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Found 7 papers, 0 papers with code
Anatomy of Industrial Scale Multilingual ASR
This paper describes AssemblyAI's industrial-scale automatic speech recognition (ASR) system, designed to meet the requirements of large-scale, multilingual ASR serving various application needs.
Two-pass Endpoint Detection for Speech Recognition
Endpoint (EP) detection is a key component of far-field speech recognition systems that assist the user through voice commands.
Separator-Transducer-Segmenter: Streaming Recognition and Segmentation of Multi-party Speech
Finally, we establish a novel framework for segmentation analysis of multi-party conversations through emission latency metrics.
Multi-turn RNN-T for streaming recognition of multi-party speech
Second, we propose a novel multi-turn RNN-T (MT-RNN-T) model with an overlap-based target arrangement strategy that generalizes to an arbitrary number of speakers without changes in the model architecture.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Streaming Multi-speaker ASR with RNN-T
Recent research shows end-to-end ASR systems can recognize overlapped speech from multiple speakers.
Improving RNN-T ASR Accuracy Using Context Audio
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 exploit context audio from a stream, using segmented or partially labeled sequences of the stream during training.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Analysis of Deep Clustering as Preprocessing for Automatic Speech Recognition of Sparsely Overlapping Speech
In a more realistic ASR scenario the audio signal contains significant portions of single-speaker speech and only part of the signal contains speech of multiple competing speakers.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
