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Found 7 papers, 2 papers with code
Contrastive Siamese Network for Semi-supervised Speech Recognition
This paper introduces contrastive siamese (c-siam) network, an architecture for leveraging unlabeled acoustic data in speech recognition.
Turn-to-Diarize: Online Speaker Diarization Constrained by Transformer Transducer Speaker Turn Detection
In this paper, we present a novel speaker diarization system for streaming on-device applications.
Reducing Streaming ASR Model Delay with Self Alignment
From LibriSpeech evaluation, self alignment outperformed existing schemes: 25% and 56% less delay compared to FastEmit and constrained alignment at the similar word error rate.
Transformer Transducer: One Model Unifying Streaming and Non-streaming Speech Recognition
In this paper we present a Transformer-Transducer model architecture and a training technique to unify streaming and non-streaming speech recognition models into one model.
Transformer Transducer: A Streamable Speech Recognition Model with Transformer Encoders and RNN-T Loss
We present results on the LibriSpeech dataset showing that limiting the left context for self-attention in the Transformer layers makes decoding computationally tractable for streaming, with only a slight degradation in accuracy.
Toward domain-invariant speech recognition via large scale training
More importantly, such models generalize better to unseen conditions and allow for rapid adaptation -- we show that by using as little as 10 hours of data from a new domain, an adapted domain-invariant model can match performance of a domain-specific model trained from scratch using 70 times as much data.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Speech recognition for medical conversations
We explored both CTC and LAS systems for building speech recognition models.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
