Speech Recognition Software

What is speech recognition software?

Speech recognition software (aka voice recognition software) enables computers to interpret human speech and transcribe that speech to text, and vice versa. Speech recognition software can also power personal virtual assistants, facilitating voice commands that prompt specific actions. Speech recognition software applications include interactive voice response (IVR) systems, which route incoming calls to the correct destination based on customer voice instructions.

The benefits of speech recognition software

• Faster documentation: According to a Stanford study, taking notes via dictation is three times faster than typing. Speech recognition solutions free up users to focus on important tasks rather than taking notes. As an example, medical practitioners can document patient visits/appointments without having to manually record each note. Customer service agents can document calls without typing, letting agents speed up the entire process of helping customers and improving overall customer service quality.
• Efficient note-taking: A common misconception around speech recognition solutions is that such tools are error-prone. However, as speech recognition systems approach near-human levels of accuracy, this concern has become virtually nonexistent. In fact, users now look at these solutions as a way to improve accuracy in their note-taking and documentation processes.

Typical features of speech recognition software

• Audio Capture: Record audio or import/upload audio files into the system.
• Automatic transcription: Transcribe voice messages and audio files.
• Multi-language: Recognize and support multiple languages/dialects.
• Speech-to-text analysis: Analyze, correct, and monitor speech for transcriptions or recordings.
• Text editor: Review transcribed text and make basic corrections (e.g., fix typos).

Considerations when purchasing speech recognition software

• Mobile app: The proliferation of smartphones has turned mobile devices into indispensable business assets. As in other markets, mobile applications have made their way into the speech recognition software space with apps that let users take notes while on the go. Users can also connect mobile devices to bluetooth headsets and headphones with a microphone to facilitate easy dictation. Businesses with mobile workforces should shortlist products that offer mobile app functionality.
• Industry-specific needs: To maximize any speech recognition solution, you should use a system with features that meet your industry needs. Some speech recognition products are better-suited for specific industries. For example, medical practices require voice recognition solutions that support medical terminologies. Buyers should evaluate products that fit their industry-specific needs—including reading user reviews—and shortlist accordingly.
• Total cost of ownership (TCO): As shown in the pricing section above, speech recognition solutions are available in a variety of pricing models. Since the myriad of options can make direct pricing comparison difficult, buyers should estimate their business’ needs by calculating their number of words, audio duration, and user number to determine the TCO. Buyers should then use this estimated TCO to shortlist products based on their actual budget.

Relevant speech recognition software trends

• Speech recognition will integrate with smart devices: The internet of things (IoT) is one area where speech recognition software holds immense promise. Speech recognition software that integrates with IoT mobile applications lets users control smart devices using voice instructions. As speech recognition solutions become more and more accurate while businesses continue to embrace the IoT, expect to see increased integration between the two within the next five years.
• Voice-based bots is the next big thing: Another area where speech recognition technology holds promise is chatbots. When integrated with speech recognition technology, chatbots can emulate human conversations in customer-facing communications by listening to customer queries, interpreting them, and making recommendations. In the same way businesses have started using chatbots, expect similar adoption of voice-based bots within the next five to seven years.