#speech-to-text

NISQA is a deep learning model/framework for speech quality prediction. The NISQA model weights can be used to predict the quality of a speech sample that has been sent through a communication system (e.g telephone or video call). Besides overall speech quality, NISQA also provides predictions for the quality dimensions Noisiness, Coloration, Discontinuity, and Loudness to give more insight into the cause of the quality degradation.

another dictation tool like superwhisper

One of Deepgram’s goals for the upcoming year is to pass the Audio Turing Test, which assesses how realistic and human-like AI-generated audio sounds.

Voxtral Realtime - A 4 billion parameter model aimed at live transcription, achieving “state of the art” transcription with 480ms latency across 13 languages. It can be configurable down to sub-200ms latency.

Performance on the FLEURS benchmark shows that Voxtral Mini Transcribe V2 performs competitively against models from Gemini and OpenAI, with the lowest diarization error rate.