Asr

A week ago, we released Koyal: open speech transcription models for Hindi, Kannada, Malayalam and Telugu. The official post has all the details. This is my personal side of it, plus a small script so you can try it on your own recordings today. Why Koyal matters to me I’ve believed every language deserves tools built for it, and small open models are how that becomes real. You can download them, run them yourself, and adapt them without depending on anyone’s API. [Read More]

The research carried out as part of my PhD was centred around the linguistic challenges in Malayalam speech recognition. One of the biggest chellenges associated with recognizing speech in morphologically complex languages is centred around how granular should be the text tokens. Classical ASR with Word tokens In the classical architecture of Automatic Speech Recognition (ASR) with word tokens, the acoustic model identifies fundamental sound units, the pronunciation lexicon maps sounds to words, and the language model predicts word sequences to convert speech to text. [Read More]

Malayalam speech recognition model trained on various openly available speech and text corpora using Kaldi toolkit is now released here. It is now available for testing on the Vosk-Browser Speech Recognition Demo website. This Malayalam model can be used with Vosk speech recognition toolkit which has bindings for Java, Javascript, C# and Python. A speech recognition architecture that works best in scenarios of limited speech data availability is called a pipeline model, where it is composed of an acoustic model, a language model and a phonetic lexicon. [Read More]