Search Results for author:
Found 12 papers, 3 papers with code
Isochrony-Controlled Speech-to-Text Translation: A study on translating from Sino-Tibetan to Indo-European Languages
End-to-end speech translation (ST), which translates source language speech directly into target language text, has garnered significant attention in recent years.
TransVIP: Speech to Speech Translation System with Voice and Isochrony Preservation
There is a rising interest and trend in research towards directly translating speech from one language to another, known as end-to-end speech-to-speech translation.
CoVoMix: Advancing Zero-Shot Speech Generation for Human-like Multi-talker Conversations
In this paper, we introduce CoVoMix: Conversational Voice Mixture Generation, a novel model for zero-shot, human-like, multi-speaker, multi-round dialogue speech generation.
Adapting Multi-Lingual ASR Models for Handling Multiple Talkers
State-of-the-art large-scale universal speech models (USMs) show a decent automatic speech recognition (ASR) performance across multiple domains and languages.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Target Sound Extraction with Variable Cross-modality Clues
Automatic target sound extraction (TSE) is a machine learning approach to mimic the human auditory perception capability of attending to a sound source of interest from a mixture of sources.
Target Speaker Voice Activity Detection with Transformers and Its Integration with End-to-End Neural Diarization
This paper describes a speaker diarization model based on target speaker voice activity detection (TS-VAD) using transformers.
Leveraging Real Conversational Data for Multi-Channel Continuous Speech Separation
In this paper, we propose a three-stage training scheme for the CSS model that can leverage both supervised data and extra large-scale unsupervised real-world conversational data.
PickNet: Real-Time Channel Selection for Ad Hoc Microphone Arrays
Since PickNet utilizes only limited acoustic context at each time frame, the system using the proposed model works in real time and is robust to changes in acoustic conditions.
All-neural beamformer for continuous speech separation
Recently, the all deep learning MVDR (ADL-MVDR) model was proposed for neural beamforming and demonstrated superior performance in a target speech extraction task using pre-segmented input.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
VarArray: Array-Geometry-Agnostic Continuous Speech Separation
Continuous speech separation using a microphone array was shown to be promising in dealing with the speech overlap problem in natural conversation transcription.
Continuous Speech Separation with Ad Hoc Microphone Arrays
Prior studies show, with a spatial-temporalinterleaving structure, neural networks can efficiently utilize the multi-channel signals of the ad hoc array.
Neural Speech Separation Using Spatially Distributed Microphones
The inter-channel processing layers apply a self-attention mechanism along the channel dimension to exploit the information obtained with a varying number of microphones.
