Vocapia Research develops core multilingual large vocabulary speech
recognition technologies* for voice interfaces and automatic audio
indexing applications. This speech-to-text technology is available for multiple languages. (* Under license from LIMSI-CNRS)
The targeted users and customers of speech-to-text transcription
technologies are actors in the multimedia and call center sector,
including academic and industrial organizations interested in the
automatic mining processing of audio or audiovisual documents.
This core technology can serve as the basis for a variety of applications: multilingual audio indexing, teleconference transcription, telephone speech analytics, transcription of speeches, subtitling…
Large vocabulary continuous speech recognition is the key technology for
enabling content-based information access in audio and audiovisual
documents. Most of the linguistic information is encoded in the audio channel of
audiovisual data, which once transcribed can be accessed using
Via speech recognition, spoken document retrieval can support random
access using specific criteria to relevant portions of audio documents,
reducing the time needed to identify recordings in large multimedia
databases. Some applications are data-mining, news-on-demand, and
The Vocapia Research speech transcription system transcribes the speech segments located in an audio file. Currently systems for 17 languages varieties are available for broadcast and web data. Conversational speech transcription systems are available for 7 languages.
The transcription system has two main components: an audio partitioner and a word recognizer.
The audio partitioner divides the acoustic signal into homogeneous segments, and associates appropriate (document internal) speaker labels with the segments.
For each speech segment, the word recognizer determines the sequence of
words, associating start and end times and a confidence measure for each
PC with Linux platform (via licensing uses).
The VoxSigma software is available both via licensing and via our Web service.