Speech Recognition

What is speech recognition?

Speech recognition, also referred to as automatic speech recognition (ASR), computer speech recognition, or speech-to-text, is a computer’s ability to recognize and translate spoken language into text.

However, voice recognition software uses speech recognition algorithms to convert spoken language into text. Businesses use this software for dictation or converting audio and video files to text. 

Additionally, these tools can be used in customer service to process routine phone requests. They help companies improve communications and translate them into an easily-managed and searchable data format.

How does speech recognition work?

Speech recognition software breaks down the audio of a recording into individual sounds. It then analyzes each sound and uses an algorithm to predict the most probable word fit in that language. Finally, the sounds are transcribed into text.

This software relies on natural language processing (NLP), machine learning, and deep learning neural networks for this process.

Key features of speech recognition

The best kind of speech recognition systems learn as they go and evolve responses with every interaction. They’re also customizable and make it possible for users to input specific requirements, such as nuances of speech. Other features include:

• Language weighting: Terms that are spoken frequently, such as product names, are weighted to improve precision.
• Speaker labeling: In multi-person conversations, individual contributions are labeled.
• Profanity filtering: Identifies certain inappropriate words or phrases that can be filtered out of speech.
• Acoustics training: The system can adapt to different acoustic environments and speaker styles, such as volume and voice pitch. 

Benefits of speech recognition

While speech recognition technology has been around for decades, today’s technology is more advanced than ever. Most software can detect accents and even spell complete words. Speech recognition software is beneficial because it:

• Decreases billable hours and saves money traditionally spent on a transcriptionist.
• Improves productivity and provides a more streamlined workflow for team members.
• Includes built-in terminology designed to help save time.
• Reduces repetitive tasks so professionals can focus on other aspects of their business.
• Saves money by automating and performing administrative tasks more quickly.
• Increases overall efficiency with hands-free artificial intelligence.
• Detects accents and spells words accurately.
• Can be used in many industries.

Applications of speech recognition

Speech recognition technology, which was first widely used in cell phones, is now in homes and workplaces. Some of the main applications of speech recognition include:

• Banking: Banks rely on speech recognition technology to reduce the need for human customer service, which lowers employee costs. This technology also helps customers quickly gather information or complete a transaction.
• Business: Using speech recognition technology in the workplace has increased efficiency as digital assistants perform tasks traditionally completed by humans, such as scheduling meetings, recording minutes, or searching for documents on a computer.
• Marketing: Voice search is becoming just as popular as written search, which encourages more conversational searches. Marketers can lean into this trend by staying on top of long-tail keywords and producing conversational content.
• Healthcare: Having hands-free access to medical information is a significant advantage over traditional paper records. Healthcare workers now have quicker access to medical records and specific procedural instructions, which may prove crucial when providing patient care.
• Language learning: Speech recognition technology removes language barriers. Without these barriers, there are more opportunities for people from different countries to collaborate and innovate.
• Greater accessibility for disabled people: Speech recognition technology benefits disabled people as it can generate closed captioning of conversations. Typically, this technology is used in conference rooms, classrooms, and religious services.
• In-car systems: Manual controls in cars have been replaced by speech recognition technology, allowing users to perform voice commands to select a radio station, play music from a compatible device, or initiate a phone call. 

Speech recognition vs. voice recognition 

Speech recognition identifies the words a speaker says, while voice recognition recognizes the speaker’s voice. Additionally, speech recognition takes normal human speech and uses NPL to respond in a way that mimics a real human response.

Voice recognition technology is typically used on a computer, smartphone, or virtual assistant and uses artificial intelligence (AI) to recognize and decode human patterns and respond. Voice recognition plays a key role in allowing for security features like voice biometrics.