Speech AI enables computers and other devices to understand and reproduce human speech. Today the technology becomes more and more popular across many industries. It is used to build voice-enabled and speech processing applications, automate meeting transcriptions and many more.
Voice activity detection (VAD) allows us to identify the presence or absence of human speech. It is a vital component for the majority of Speech AI solutions. For instance, VAD is used to enable speech commands in various smart devices or build speech-processing applications.
Automatic speech recognition (ASR) is a technology that converts spoken language into text. It is used to transcribe audio recordings, enable voice commands in different languages or identify multiple speakers. ASR has already become the gateway to AI-driven interactive products and services like virtual assistants or smart devices.
The technology allows modification of a speaker's voice without impacting the text of the original recording. Such a transformation can be done in two ways: cloning and effects overlaying. It is often used to dub series, movies or games into another language, as well as to build a variety of translation applications.
This technology labels audio recordings with corresponding timestamps that define boundaries between different speakers. Each segment is associated with a particular speaker. Their gender or age can also be detected. Speaker diarization and identification are an important part of any speech analytics application.
This technology can analyze what you say and how you say it by focusing on sounds, not words. Besides speech analysis on a phoneme level, it includes an advanced scoring system on top, followed by detailed visualized feedback. This makes it not only a critical component of an ASR system but also a basis for building pronunciation applications.
Take a look at one of our successful cases