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Found 8 papers, 2 papers with code
An Experimental Review of Speaker Diarization methods with application to Two-Speaker Conversational Telephone Speech recordings
We found that, among all methods considered, EEND-vector clustering (EEND-VC) offers the best trade-off in terms of computing requirements and performance.
End-to-End Integration of Speech Separation and Voice Activity Detection for Low-Latency Diarization of Telephone Conversations
Finally, we also show that the separated signals can be readily used also for automatic speech recognition, reaching performance close to using oracle sources in some configurations.
Conversational Speech Separation: an Evaluation Study for Streaming Applications
Continuous speech separation (CSS) is a recently proposed framework which aims at separating each speaker from an input mixture signal in a streaming fashion.
Low-Latency Speech Separation Guided Diarization for Telephone Conversations
In particular, we compare two low-latency speech separation models.
Audio-Visual Speech Inpainting with Deep Learning
In this paper, we present a deep-learning-based framework for audio-visual speech inpainting, i. e., the task of restoring the missing parts of an acoustic speech signal from reliable audio context and uncorrupted visual information.
Audio-Visual Target Speaker Enhancement on Multi-Talker Environment using Event-Driven Cameras
In order to overcome this limitation, we propose the use of event-driven cameras and exploit compression, high temporal resolution and low latency, for low cost and low latency motion feature extraction, going towards online embedded audio-visual speech processing.
An Analysis of Speech Enhancement and Recognition Losses in Limited Resources Multi-talker Single Channel Audio-Visual ASR
In this paper, we analyzed how audio-visual speech enhancement can help to perform the ASR task in a cocktail party scenario.
Face Landmark-based Speaker-Independent Audio-Visual Speech Enhancement in Multi-Talker Environments
In this paper, we address the problem of enhancing the speech of a speaker of interest in a cocktail party scenario when visual information of the speaker of interest is available.
Ranked #1 on
Speech Enhancement
on GRID corpus (mixed-speech)
