Speech Recognition Software

Have you ever realized how human communication and speech has evolved over several centuries? From displaying symbols and images to portraying information to the emergence of the internet, smartphones, and other digital communication formats, human interaction has undergone an enormous change.  

The progression of technology has also transformed speech with voice control's sophistication, such as introducing the voice assistant. But another popular term, which has become a buzzword - Speech recognition software, enables companies to mechanize and streamline business processes. The speech recognition tools are also easily accessible, cost-effective, and user-friendly. 

The following buyer’s guide takes you through a comprehensive journey on speech recognition and its essential tools. You will also learn about the software’s core features, benefits, popular applications, recent trends, and more details.

In simple terms, speech recognition is the ability of a machine or device to understand spoken words and phrases. The language gets translated into a machine-readable format. 

You can take the example of a microphone that records your voice and a hardware program converts sound from analog to digital. The software helps to process the audio data and interpret the sound as individual words. 

Speech recognition has also been identified as a subcategory of computational linguistics through computers recognizing the text language. You can even refer to it as computer speech recognition or automatic speech recognition.

Before proceeding with any further details on speech recognition, it’s essential to throw some light on its brief history. 

Speech recognition dates back to 1952 when three Bell laboratory researchers developed a new system known as Audrey. The other significant development occurred in 1962 when the renowned multinational technology company IBM demonstrated and built a Shoebox machine that could distinguish between 16 spoken words in English. 

During the period 1970-1990, various successful studies and research were carried out in different parts of the world. For instance, DARPA started working on a Speech Understanding Research Program with a quest to find a minimum vocabulary size of 1000 words. In the mid-1980s, the IBM developers developed a voice-activated typewriter Tangora, which could handle 20,000 vocabulary words. 

Next, in the 2000s, DARPA demonstrated a couple of speech recognition programs. Google’s first attempt at speech recognition came in 2007 when it built a GOOG-411, a telephone directory-based service. The device helped a great deal to improve Google’s recognition solutions. 

In 2009, Geoffery Hilton created deep feedforward networks for acoustic modeling. The early 2010s saw a clear distinction between speech recognition and voice recognition. In 2012, the speech recognition technology progressed significantly, gaining more accuracy with deep learning. This embarked, the clear beginning of a revolution. The concept of end-to-end automatic speech recognition came in 2014 with the introduction of Connectionist Temporal Classification (CTC)-based systems. 

The cloud-based solutions and digital transformation technologies have played a considerable role in consistently improving and boosting speech recognition in recent years. Thus, the ability to hear and understand the words has enhanced a lot.

So, the next question that comes to mind is, how does speech recognition work? Speech recognition first analyzes the speaker’s sound and then filters it accordingly. The next step digitizes that filtered sound and converts it into a readable format. It again analyzes the sound to understand its meaning. 

Sound recognition depends on algorithms and different models to accurately guess your words. It means it has to comprehend the speaker’s language. 

Also, if a single person uses a speech recognition device, they can adjust the settings according to their convenience. But the challenge is when the machine has to work for multiple markets. The developers must program the device accordingly to quickly identify variations, languages, dialects, and more variations. 

The developers also have to pay attention to nullifying the issue of background noise. They need to program the device so that unwanted sound gets filtered out. 

Another crucial aspect that comes into play is the sound’s signal. It is categorized into small segments that are hundredths or thousandths of a second, as in the case of plosive consonant sounds. The machine matches the details with phonemes in a formal language.   

In the next stage, one has to focus more on speech recognition research. Here you have to check phonemes in other phoneme contexts. The related phoneme is passed through a complex statistical model, comparing them to a broad set of words, phrases, and sentences. The program sends the output in the form of text or computer commands.

The experts believe that speech recognition didn’t reach a hundred percent accuracy. Thanks to the innovative technology, it is attaining almost 98% accuracy in the current scenario. Hence, the prime target of speech recognition is to maximize accuracy and speed. Indeed, the developers aim to improve speech recognition efficiency, which can even surpass human capabilities. It also allows them to save a lot of valuable time. 

Speech recognition helps a computer or device identify and understand spoken words without focusing on other details such as cadence, accent, or more. It provides enhancing user experience and improves the self-service containment rate. 

It delivers a natural human-like interaction to increase self-satisfaction when interacting with the machines. It enables the companies to collect the customers’ dynamic data, such as their names, addresses, and other information. 

Of late, speech recognition has also been playing a part in simplifying complicated IVR menus. It is expected that with time and the escalation of technology, speech recognition will play a more vital role in society.

Speech and voice recognition are innovative next-generation technologies catering to various industries and applications. They may appear similar on paper, but they are two different functions of virtual assistants. Yes, there is a varied difference between the two technologies. 

Let’s compare the key differences between speech and voice recognition in a table format.

Speech-to-text is yet another term for speech recognition. It is an advanced technique that utilizes speech recognition technology to identify the audio signals, sound waves, and patterns, match them with the phonemes, and then convert them into text. 

Speech-to-text is a vital asset for business organizations, irrespective of their sizes. This is why most entrepreneurs gradually show a keen interest in investing in viable speech-to-text software. The tools enable companies to unleash a plethora of benefits, such as.

• Streamlining the Communication Process-  One of the unique selling points of Speech-to-text is that it simplifies communication. Yes, interaction becomes much more accessible. There is no need for any handwritten notes or documents. 
• Makes the Remote Work Location Flexible- Most companies encourage the work-from-home or remote work location policy. The speech-to-text technology supports live podcasts and webinars so that employees can attend live conferences even from a distant place. It increases employee flexibility. 
• Timesaving and Paperless Work- Speech-to-text is a digital solution that can save valuable time by eliminating tedious paper-related work. 
• Speech-to-Text is Both Swift and Convenient- Another reason speech-to-text has gained more imputes is that the technology is faster and more convenient. The speech-to-text tools can easily translate a lengthy document or paragraph in a few minutes to seconds. It can be accessed through various devices, such as mobile applications. 
• Quick Sharing of the Documents- The employees can easily share documents in real time across various devices. It helps the concerned team make smart critical decisions and improve business strategies to lead the way front. 
• Enhancement in the Workflow Process- Speech-to-text improves workflow management, where employees can set and manage priority tasks and quick turnarounds. 
• Few Chances of Creating Mistakes- With speech-to-text technology, there are few chances of committing mistakes. The advancement of technology is getting better at improving the accuracy of translated words. 
• Secured Transmission of Information- Speech-to-text technology provides a safe and secure passage for the transmission of information. It means that crucial information does not leak out.

It has been indicated earlier that various studies and research have been carried out on speech recognition to make the technology more accurate and productive. 

It must also be noted that the language, acoustic, and lexicon models are traditional or conventional speech recognition methods. 

The language model identifies which sequences of words are spoken more than the others while reading a text. Also, it helps in anticipating the words that will follow the current set of words. 

The acoustic model is based on the acoustics of the speech. The audio signal gets divided into small frames, precisely 25ms in length. The acoustic model then predicts the sound and phoneme spoken from a device in each audio segment. 

The lexicon model is related to the pronunciation of phonetic words. The phonetic experts set the phonemes specifically for that language using a phone. The lexicon model also contains specific terms having multiple pronunciations. 

Hidden Markov Models

Hidden Markov Models (HMMs) are widely used speech recognition models and algorithms. They are used in various applications. 

The Hidden Markov Model is related to modern general-purpose speech recognition technology. The HMM is a statistical model containing a series of quantities or symbols. HMM is integral to speech recognition because it comprises two types of speech stationary signals; piecewise and short-time. For example, you can process an approximately ten milliseconds static signal in a short-time scale. 

The other benefit of the Hidden Markov Model is that it is user-friendly and provides automatic training. HMM, models the system as a Markov process where X indicates unobserved or hidden states. HMM presumes another process Y, whose behavior depends on X. HMM aims to learn about X by observing Y. Hidden Markov Models are pretty popular in temporal pattern recognition and reinforcement learning. There are wide-ranging such as gesture recognition, speech handwriting, musical score following, and much more. 

Recurrent Neural Network Transducers or RNN

The Recurrent Neural Network Transducers is an artificial neural network used widely in natural language processing (NLP) and speech recognition. RNN helps identify the following characteristics and uses patterns to anticipate the following likely scenario. RNN is also used in deep learning, which helps stimulate the human brain's neurons. 

Dynamic Time Warping (DTW) 

Another popular speech recognition model or algorithm is Dynamic Time Warping. It was previously used for speech recognition, but the modern Hidden Markov Model has recently been replaced. It is an age-old model of speech recognition. 

Dynamic Time Warping measures the similarity between two sequences, which can differ in speed and time. For instance, you can use DTW to identify the similarities in activities, such as observing the walking patterns of two persons. Dynamic Time Warping also applies to various audio, video, and graphics applications. DTW analyzes any data which you can convert to linear representation. DTW is also relevant to automatic speech recognition to match the different speaking speeds.  

Neural Networks

Neural networks are also an acoustic modeling approach applied to various aspects of speech recognition. These include categorizing the phonemes, categorizing the phonemes via multi-objective scalable algorithms, audio-visual speaker recognition, audio-visual speech recognition, and more. It is also referred to as Artificial Neural Networks (ANN). 

The neural network is also an old-school speech recognition method, which was introduced in 1958.

End-to-End Acoustic Speech Recognition

End-to-End Acoustic Speech Recognition Is a newly introduced speech recognition model. It is an advanced approach that focuses on jointly learning all speech recognition components. The training process in end-to-end models is more straightforward than in the Hidden Markov Model. 

The introduction of Connectionist Temporal Classification proved crucial for automatic speech recognition. It comprises Recurrent Neural Networks and CTC layers. The recurrent neural networks and the CTC model learn the acoustic model and pronunciation together but cannot determine the language. 

Deep Neural Networks

The Deep Neural Network, or DNN, is an artificial neural network with various remote unit layers. It is a complicated model with non-linear relationships. DNN also builds compositional models having additional layers. These layers allow architecture lower-layer features, which helps a proper scope of learning.

The speech recognition technology has undergone a lot of changes and improvements during the last few years. The experts are focusing more on bringing speed and accuracy. Speech recognition has indeed progressed with the emergence of digital technologies, but it has also tackled a few challenges. 

The experts believe that two primary factors cause issues related to speech recognition. They are loud and noisy environments and reach. But there are few other speech-recognition challenges, which are discussed below. 

• Noisy and loud background sounds- One of the critical concerns of speech recognition in noisy and loud environments. The different devices, such as microphones, cannot record the spoken words accurately. Often you may need an additional mechanism to support them. 
• Data security- The devices, while understanding and translating the spoken words, gather massive amounts of data, which can be utterly confidential. Any lapse in data security can cost a company dearly. 
• Incorrect interpretations- Another critical challenge is inaccuracy in identifying the speech. At times, the machines cannot understand complicated jargon and phrases, failing to translate it into a readable format. 
• Different kinds of accents- Different types of accents are a concern for machines and devices. Take, for example, the American English accent is different from British accents. As a result, the commands are not able to function correctly.
• Lack of time and efficiency- In some cases, speech recognition can be a time-consuming process as some words may not come across well. The machines may not be able to transliterate words that are spoken too fast or have a peculiar tone. 

One of the optimal ways to handle these challenges and eliminate the concerns is implementing the best speech recognition software. So, let’s start first by defining the tool. 

Speech recognition software is an innovative and cutting-edge technology that enables a computer machine or device to input spoken words and translate them into written text. 

Speech recognition software also empowers different virtual assistants to facilitate voice commands. The software tools may include an IVR system that transfers incoming calls to the correct destination based on customer requirements. The tools are pre-equipped with various commands allowing the user to carry out different tasks. Some versions of a few software enable programmers to create custom commands.

One core aspect that makes speech recognition software unique and distinct is the typical features. Let’s highlight the crucial ones.

• Audio capture- Speech recognition tools allow you to capture audio recordings and reduce the noisy environment. The software enables the machines or devices to record or capture the audio accurately that you can transfer easily. 
• Automatic transcription- The automated speech recognition software can transform any audio or video file into a written text. It enhances the experience of the audience and is used in a diverse set of industries. 
• Concatenated speech- One of the unique features of speech recognition systems is attached speech. It allows you to slice together the recorded or synthesized words to create an answer between a machine and a person. 
• Custom dictionary-  Speech and voice recognition software provide a custom or personalized dictionary you can add to the machine. For instance, if you are related to the healthcare sector, you can add medical terms to the machine. 
• Customizable macrons- Some leading speech recognition software, such as Windows Speech Recognition, support custom macros with the help of supplementary applications enabling natural language commands. For example, Microsoft has released email macrons. 
• Multi-lingual support- Speech recognition tools provide multi-language support. It means you can recognize and transcribe your voice in various popular languages. You can add paragraphs, add punctuation marks, and special characters. 
• Speech-to-text analysis- With the speech-to-text analysis feature, you can translate an entire audio recording into the text, discovering the root causes of customer interaction. 
• Voice recognition- is a feature that receives and interprets a dictation to carry out spoken commands. Voice recognition has become more innovative with the rise of artificial intelligence. 
• Speech recording- The speech recognition system has a speech recording facility that allows you to confirm the words spoken. It means you can compare the words with the text on the screen. Also, it has a playback correction option that allows you to amend the words quickly. 
• Text-to-speech analysis- Text-to-speech is a central feature that proves handy while proofreading. Some speech recognition tools provide this facility. You can listen to the text and synthesize the text-to-speech engine. For instance, in Dragon NaturallySpeaking, you can use commands such as ‘Read Paragraph,’ ‘Read Down From Here,’ and more. 
• Natural language commands- Natural language commands is a unique feature that involves speech recognition and voice recognition software characteristics. You can use the advanced natural command syntax to manipulate the text quickly and control the applications. The natural language commands are helpful while working on MS Word Docs. You can use the commands such as ‘Bold the Text,’ ‘Make it New Times Roman,’ and ‘Bullet this Paragraph.’
• Choose and say dictation- One of the exclusive features of the top speech recognition software is ‘choose and say dictation.’ This feature lets you dictate, edit, and correct using voice in MS Word Docs. Dictating over the top is both faster and easier. But you cannot use this feature for all the programs. Also, you may need a proper word processor for dictating the text. 
• A rich set of vocabulary- The Speech Recognition Software provides you with a rich set of language, all stored in the software. You can use the vocabulary to translate the text and correct the misunderstood words. The tool also allows you to personalize your vocabulary by adding technical terms or other names. 
• Text macros and diction shortcuts- This feature is helpful if you are using standard words and phrases. The software allows you to store and type the text using short commands. You can download this feature for free in Microsoft Windows Speech Recognition Macros. 
• Assign someone for corrections-  The speech recognition software and the voice recognition tool enable you to delegate someone to make corrections. It means you can dictate the text and then assign a professional to correct it on a later note. The appointed person has to record his speech and save it with the documents. It provides you with the scope of third-party correction once the transcription has been created.  
• Compatible with mobile devices- Speech and voice recognition systems are compatible. It means that you can work while on the move.

There is no denying that speech recognition software is an innovative and ever-evolving tool. Speech recognition has led to the growth of digital assistants helping carry out basic and simple tasks. It enables you to access massive amounts of information in real time using digital sources. Hence, speech recognition software has gained widespread applications. It has disrupted a wide range of industries and business domains.  

• The Healthcare Sector- The medical and healthcare sector uses speech recognition tools to unleash various benefits. For instance, it helps healthcare professionals to access medical records in real time. The nurse and medical staff become aware of specific instructions, including administrative information. The patient’s family is familiarized with what stage the patient needs to be admitted to the hospital. 
• The Banking and Finance Sector- Do you know that many banks have already facilitated the payment and transaction process through Apple’s Siri or Amazon Alexa? Yes, banks are embracing voice technology, intending to provide more convenience to their customers. Customers can even check their balances and recent transactions in a quick time. 
• The Retail Industry- The retail industry is capitalizing on speech recognition software. Credit must go to Amazon’s suite of Echo devices, such as Alexa, streamlining and amplifying the customer’s shopping experience. Customers can order and reorder many products, even without using their fingers. They can also easily find any product without wasting their valuable time.  
• Transportation Industry-  Of late, customers have been using Alexa or Siri to book a cab on Uber. Also, a few companies are working to integrate voice-assisted technology with public transport. Using this technology, the user can easily find the next train or bus available for a particular destination. 
• Media and entertainment industry- Media and entertainment industry is not lacking behind in reaping the advantage of speech recognition tools. The software significantly helps to reduce the editing time and make the editing process more accurate. Also, it enables media organizations to manage various assets efficiently. It also helps in media monitoring, captioning, and subtitling. 
• Workplaces- The professionals can search for various reports and documents. The managers can use speech-to-text software to dictate the text that needs to be filed in the paper. The software can schedule meetings, record minutes, and create presentations and graphics. Also, the tools help to make travel arrangements. Voice technology has simplified many repetitive HR tasks, specifically during recruitment.   
• Marketing- Marketers get access to new marketing data and current market trends quickly to analyze the customer’s demands. Also, marketers can use the consumer’s accent, vocabulary, and speaking pattern to identify their location, age, and other essential details. In short, speech recognition software enables businesses to increase their customer base. 
• Search engine- Speech recognition systems play a pivotal role in helping users to find appropriate information that they are looking for in search engines. Hence, the software is crucial from the SEO perspective as well. Business enterprises can thus improve their search rankings and drive more traffic. 
• IoT- The Internet of Things aligns with speech recognition tools allowing users to listen to hands-free messages and control the radio tuning. It also plays a supportive role in navigation and guidance and responds to voice commands. 
• Crime Investigation- Speech recognition software has become a worthy asset to help police and investigating agencies investigate crime. It can help to identify the voice samples and match them with different persons to solve cases. 
• Education- Speech recognition is helpful while learning a second language. It enables students to learn proper pronunciation and develop their speaking skills. Also, students without vision can use this technology to convey and recite words after listening. They can use their voice to command the computer. Students with injuries don’t have to think about handwriting or typing. Speech recognition enables students with disabilities to become improved writers.

In addition to these popular applications, one can implement speech recognition in various fields, such as learning a language, delivering services, voice-controlled games, and apps. Also, the software proves its worth in-car systems, the military, defense service, home automation, robotics, and many more. 

The speech recognition software caters to diverse industries providing a wide array of benefits. The various advantages of the speech recognition system are as follows-

• Promotes hands-free technology- While working on an assignment or project, the speech recognition software enables you to take easy notes and use other devices without using your hands. Imagine using Apple Siri or Google Maps to reach your desired destination. Think about the valuable time that hands-free technology saves, which you can utilize for other tasks. 
• Helps to control digital devices- Speech recognition tools use machine learning and artificial intelligence technologies to understand spoken words better. You can gain more control over digital assistants such as Google Home, Alexa, or Siri with the correct pronunciation. Signal processing helps to establish an improved understanding between humans and machines. 
• Fast and accurate- The best speech recognition software is quick and precise. Most people speak faster than they write; the software efficiently translates words into a document. The tools can help make the documents error-free, providing more accurate and reliable results.  
• Serves many industries- One has already witnessed how speech recognition software has fueled wide-ranging sectors, from banking, finance, retail, healthcare, media, transport, education, and many more. The speech-to-text software can be incorporated irrespective of business size and domain. 
• A decrease in paperwork- Speech recognition tools promote the creation of electronic documents, eliminating paperwork usage. You have to communicate with the computer or device, and the results are displayed in different applications such as MS Word. Also, Bluetooth provides an additional benefit where you can easily communicate with wireless technology. 
• Aid for the hearing impaired- The speech recognition tool and voice recognition software has blessed hearing-impaired persons. They can take support and help from text-to-speech and dictation systems. The audio gets converted into text, which acts as a critical tool for the communication process. 
• Automation of the workflow- Speech recognition systems do more than translate speech into readable text. It also plays a crucial role in workflow automation, where you can complete tasks more efficiently. You can voice command applications to create files, schedule meetings, and send emails. It also improves searchability on search engines, helping gather precise information on a topic. 

Speech recognition software is characterized by both speed and accuracy. It is known for providing high performance and is regarded as the optimal alternative to traditional document typing. Speech recognition applications allow you to create documents at 160 words per minute, almost three times quicker than typing. The output is shown on different applications when users interact with the machines. 

The use of wireless and hands-free technology, such as Bluetooth, further accelerates the speed of dictation. It simply means that the users can free their hands while taking notes. They can also freely move around while dictating the text and getting additional references or information on the trot. 

Notably, speech recognition software offers a 99% accuracy right away. It provides an exclusive vocabulary list for various sectors such as marketing, finance, taxation, insurance, public transport, etc. 

For example, with Google’s progress and speech recognition innovation, accuracy has almost improved since 2013. The company has worked on important aspects such as calculating the word’s error rate using real-world search data. Since accuracy is getting better, it is further leading to increased productivity. 

We are already in 2020, and speech recognition software has created a buzz worldwide. The number of respondents using this innovative software is ever-increasing, while many others are considering implementing this tool into their businesses. Hence, it poses a bright and promising future ahead. 

• Mobile payments using speech recognition- You will use your voice to make payments in the future. Although it is in the natal stage, it will undoubtedly boom in the upcoming years. Speaking a one-time password instead of typing the PIN or credit card information would be best. 
• AI to become more innovative- Artificial intelligence-based assistants are getting more intelligent with improved neural networks. Make more accurate predictions and guesses, such as getting the right directions while driving. 
• Security to become more robust- Most Speech Recognition software vendors are working on improving safety to safeguard essential data. The software will be used for account verification or user identification. 
• Addition of more languages- Speech recognition technology is already accessible in approximately 119 words. But with the increase in smartphones, the numbers are going up. 
• Growth in the use of smart speakers- One of the other prevailing trends is an increase in the use of smart speakers. 
• More use in forensics and investigation- Speech and voice recognition software will play a more significant role in forensic and criminal investigations. The forensic team can identify the audio samples as reliable evidence. Thus, voice ID technology can be conjugated with biometrics to verify. 

Today business organizations are using speech recognition software for call-tracking activities. The tool helps to transcribe the content of audio calls that are recorded in the system. The software also provides Calltracks packages that differentiate a caller and the agent and tracks the produced transcript. 

Then there is a CallScore that automatically determines the leads and not leads. It also helps in keyword spotting, where the agents can tag the calls based on the customer's keywords. It is interesting to note that speech recognition tools can use call tracks to provide keyword research, which is important for SEO. 

Also, the transcripts allow for analyzing essential data used for customer training and support purposes. It helps businesses enhance customer experience, increase sales, and support processes.

If you have already decided to purchase and implement the best speech recognition software, you must consider a few pivotal factors to select the optimum tool. The essential aspects include the following-

• Industry-Specific Needs-  First and foremost, you must consider industry and business-specific needs. For instance, if you are a retailer or marketer, you may need a different speech recognition tool from the ones used by military and defense personnel. 
• Features and Functionalities-  Next, it is essential to consider the vital functions and features of the software. You need to check if the software offers a speech recording facility and test the tool's speed and accuracy through voice recognition software reviews. 
• Compatible with Multiple Devices- You need to ensure that your voice activation software is compatible with most devices, whether you are using a laptop, desktop, tablet, or smartphone. 
• Price-  It is a pleasure to note that there are many options for selecting the best free speech recognition software. You can also first use the trial version before subscribing to the tool according to your specific needs. 
• Support- You need to consider the type of customer support available from the concerned vendor. Most vendors offer email, and telephonic support live a few provide live chat facilities.

The cost of speech recognition software depends on various variable factors. You can even explore the top free and open source speech recognition software such as Simon, Kaldi, Mozilla, Mycroft, Dictation Bridge, and others. 

If you don't want to invest big then, check out Sonix, which costs around $10 per month. Also, there is Braina Pro for which you need to pay $49 per month. 

But the ones with more exclusive features are Dragon NaturallySpeaking, iSpeech Translator, and Speechmatics. You will have to get in touch with the concerned software vendor to know the exact pricing details.

Goodfirms is one of the most reliable and leading research and review platforms that has helped software buyers and service seekers select optimum options. It also allows IT and digital marketing companies to grow organically and boost their online presence. 

The Goodfirms team has provided a list of speech recognition software to help business organizations, government agencies, and other industry experts select the best tool based on their specific needs.