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Found 11 papers, 4 papers with code
Gull: A Generative Multifunctional Audio Codec
We introduce Gull, a generative multifunctional audio codec.
Consistent and Relevant: Rethink the Query Embedding in General Sound Separation
In this paper, we present CaRE-SEP, a consistent and relevant embedding network for general sound separation to encourage a comprehensive reconsideration of query usage in audio separation.
AutoPrep: An Automatic Preprocessing Framework for In-the-Wild Speech Data
To address this issue, we introduce an automatic in-the-wild speech data preprocessing framework (AutoPrep) in this paper, which is designed to enhance speech quality, generate speaker labels, and produce transcriptions automatically.
Complexity Scaling for Speech Denoising
A series of MPT networks present high performance covering a wide range of computational complexities on the DNS challenge dataset.
Ultra Dual-Path Compression For Joint Echo Cancellation And Noise Suppression
Echo cancellation and noise reduction are essential for full-duplex communication, yet most existing neural networks have high computational costs and are inflexible in tuning model complexity.
Bayes Risk Transducer: Transducer with Controllable Alignment Prediction
While the vanilla transducer does not have a prior preference for any of the valid paths, this work intends to enforce the preferred paths and achieve controllable alignment prediction.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
High Fidelity Speech Enhancement with Band-split RNN
Despite the rapid progress in speech enhancement (SE) research, enhancing the quality of desired speech in environments with strong noise and interfering speakers remains challenging.
Beam-Guided TasNet: An Iterative Speech Separation Framework with Multi-Channel Output
The proposed framework facilitates iterative signal refinement with the guide of beamforming and seeks to reach the upper bound of the MVDR-based methods.
Power pooling: An adaptive pooling function for weakly labelled sound event detection
While this paper focuses on sound event detection applications, the proposed method can be applied to MIL tasks in other domains.
Exploring the time-domain deep attractor network with two-stream architectures in a reverberant environment
Deep attractor networks (DANs) perform speech separation with discriminative embeddings and speaker attractors.
Integrating the Data Augmentation Scheme with Various Classifiers for Acoustic Scene Modeling
This technical report describes the IOA team's submission for TASK1A of DCASE2019 challenge.
