38 citations · 45 across the 7 of their papers we have counts for
8 papers
Anatomy of Industrial Scale Multilingual ASR
Francis McCann Ramirez, Luka Chkhetiani, Andrew Ehrenberg +14
This paper describes AssemblyAI's industrial-scale automatic speech recognition (ASR) system, designed to meet the requirements of large-scale, multilingual ASR serving various app…
Two-pass Endpoint Detection for Speech Recognition
Anirudh Raju, Aparna Khare, Di He +9
Endpoint (EP) detection is a key component of far-field speech recognition systems that assist the user through voice commands. The endpoint detector has to trade-off between accur…
Separator-Transducer-Segmenter: Streaming Recognition and Segmentation of Multi-party Speech
Ilya Sklyar, Anna Piunova, Christian Osendorfer
Streaming recognition and segmentation of multi-party conversations with overlapping speech is crucial for the next generation of voice assistant applications. In this work we addr…
Multi-turn RNN-T for streaming recognition of multi-party speech
Ilya Sklyar, Anna Piunova, Xianrui Zheng +1
Automatic speech recognition (ASR) of single channel far-field recordings with an unknown number of speakers is traditionally tackled by cascaded modules. Recent research shows tha…
Streaming Multi-speaker ASR with RNN-T
Ilya Sklyar, Anna Piunova, Yulan Liu
Recent research shows end-to-end ASR systems can recognize overlapped speech from multiple speakers. However, all published works have assumed no latency constraints during inferen…
Improving RNN-T ASR Accuracy Using Context Audio
Andreas Schwarz, Ilya Sklyar, Simon Wiesler
We present a training scheme for streaming automatic speech recognition (ASR) based on recurrent neural network transducers (RNN-T) which allows the encoder network to learn to exp…
Subword Regularization: An Analysis of Scalability and Generalization for End-to-End Automatic Speech Recognition
Egor Lakomkin, Jahn Heymann, Ilya Sklyar +1
Subwords are the most widely used output units in end-to-end speech recognition. They combine the best of two worlds by modeling the majority of frequent words directly and at the…
Analysis of Deep Clustering as Preprocessing for Automatic Speech Recognition of Sparsely Overlapping Speech
Tobias Menne, Ilya Sklyar, Ralf Schlüter +1
Significant performance degradation of automatic speech recognition (ASR) systems is observed when the audio signal contains cross-talk. One of the recently proposed approaches to…