There could be any number of speakers and final result should state when speaker starts and ends. There's probably some AWS service that does . It is based on the binary key speaker modelling technique. For many years, i-vector based audio embedding techniques were the dominant approach for speaker verification and speaker diarization applications. The Top 48 Speaker Diarization Open Source Projects Speaker Diarization - Google Cloud: AI Speech-to-Text with Python 3 Index Terms: SIDEKIT, diarization, toolkit, Python, open-source, tutorials 1. Find file Select Archive Format. Python: Speaker diarization based on Kaldi x-vectors using pretrained model trained in Kaldi (kaldi-asr/kaldi) and converted to ONNX format running in ONNXRuntime (Microsoft/onnxruntime). If you don't know machine learning and you don't have plans or time to learn it, then this is going to be exquisitely difficult. To experience speaker diarization via Watson speech-to-text API on IBM Bluemix, head to this demo and click to play sample audio 1 or 2. Who's speaking? : Speaker Diarization with Watson Speech-to-Text API Thanks to the in-session training of a binary key . It turns you can use Google speech to text API to perform speaker diarization. Diarization for ASR — s4d 0.1.0 documentation - Projets Introduction The diarization task is a necessary pre-processing step for speaker identification [1] or speech transcription [2] when there is more than one speaker in an audio/video recording. . [ICASSP 2018] Google's Diarization System: Speaker ... - YouTube Pierre-Alexandr e Broux 1, 2, Florent Desnous 2, Anthony Lar cher 2, Simon Petitr enaud 2, Jean Carrive 1, Sylvain Meignier 2. Speaker diarization is achieved with high consistency due to a simple four-layer convolutional neural network (CNN) trained on the Librispeech ASR corpus.