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Found 15 papers, 8 papers with code
Resource-Efficient Separation Transformer
Transformers have recently achieved state-of-the-art performance in speech separation.
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.
Leveraging Speech Separation for Conversational Telephone Speaker Diarization
In the online setting we consider both the use of continuous source separation (CSS) and causal SSep models architectures.
Towards Low-distortion Multi-channel Speech Enhancement: The ESPNet-SE Submission to The L3DAS22 Challenge
This paper describes our submission to the L3DAS22 Challenge Task 1, which consists of speech enhancement with 3D Ambisonic microphones.
On Using Transformers for Speech-Separation
In this paper, we extend our previous work by providing results on more datasets including LibriMix, and WHAM!, WHAMR!
Implicit Acoustic Echo Cancellation for Keyword Spotting and Device-Directed Speech Detection
In many speech-enabled human-machine interaction scenarios, user speech can overlap with the device playback audio.
Learning Filterbanks for End-to-End Acoustic Beamforming
We perform a detailed analysis using the recent Clarity Challenge data and show that by using learnt filterbanks it is possible to surpass oracle-mask based beamforming for short windows.
REAL-M: Towards Speech Separation on Real Mixtures
First, we release the REAL-M dataset, a crowd-sourced corpus of real-life mixtures.
The impact of non-target events in synthetic soundscapes for sound event detection
Detection and Classification Acoustic Scene and Events Challenge 2021 Task 4 uses a heterogeneous dataset that includes both recorded and synthetic soundscapes.
SpeechBrain: A General-Purpose Speech Toolkit
SpeechBrain is an open-source and all-in-one speech toolkit.
Ranked #2 on
Spoken Language Understanding
on Timers and Such
(using extra training data)
Learning to Rank Microphones for Distant Speech Recognition
Fully exploiting ad-hoc microphone networks for distant speech recognition is still an open issue.
Attention is All You Need in Speech Separation
Transformers are emerging as a natural alternative to standard RNNs, replacing recurrent computations with a multi-head attention mechanism.
Ranked #2 on
Speech Separation
on WSJ0-2mix
LibriMix: An Open-Source Dataset for Generalizable Speech Separation
Most deep learning-based speech separation models today are benchmarked on it.
Audio and Speech Processing
The Speed Submission to DIHARD II: Contributions & Lessons Learned
This paper describes the speaker diarization systems developed for the Second DIHARD Speech Diarization Challenge (DIHARD II) by the Speed team.
Filterbank design for end-to-end speech separation
Also, we validate the use of parameterized filterbanks and show that complex-valued representations and masks are beneficial in all conditions.
