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Found 22 papers, 7 papers with code
SpeechColab Leaderboard: An Open-Source Platform for Automatic Speech Recognition Evaluation
In this paper we introduce the SpeechColab Leaderboard, a general-purpose, open-source platform designed for ASR evaluation.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Transferring speech-generic and depression-specific knowledge for Alzheimer's disease detection
Apart from the knowledge from speech-generic representations, this paper also proposes to simultaneously transfer the knowledge from a speech depression detection task based on the high comorbidity rates of depression and AD.
DistilXLSR: A Light Weight Cross-Lingual Speech Representation Model
Multilingual self-supervised speech representation models have greatly enhanced the speech recognition performance for low-resource languages, and the compression of these huge models has also become a crucial prerequisite for their industrial application.
Task-Agnostic Structured Pruning of Speech Representation Models
Self-supervised pre-trained models such as Wav2vec2, Hubert, and WavLM have been shown to significantly improve many speech tasks.
Improving Speech Translation by Cross-Modal Multi-Grained Contrastive Learning
However, the final model often performs worse on the MT task than the MT model trained alone, which means that the knowledge transfer ability of this method is also limited.
Unsupervised Anomaly Detection and Localization of Machine Audio: A GAN-based Approach
Automatic detection of machine anomaly remains challenging for machine learning.
Cross-lingual Alzheimer's Disease detection based on paralinguistic and pre-trained features
We present our submission to the ICASSP-SPGC-2023 ADReSS-M Challenge Task, which aims to investigate which acoustic features can be generalized and transferred across languages for Alzheimer's Disease (AD) prediction.
MVKT-ECG: Efficient Single-lead ECG Classification on Multi-Label Arrhythmia by Multi-View Knowledge Transferring
However, it is challenging to develop a single-lead-based ECG interpretation model for multiple diseases diagnosis due to the lack of some key disease information.
Expressive Speech-driven Facial Animation with controllable emotions
It is in high demand to generate facial animation with high realism, but it remains a challenging task.
LMD: A Learnable Mask Network to Detect Adversarial Examples for Speaker Verification
It utilizes score variation as an indicator to detect adversarial examples, where the score variation is the absolute discrepancy between the ASV scores of an original audio recording and its transformed audio synthesized from its masked complex spectrogram.
Symmetric Saliency-based Adversarial Attack To Speaker Identification
Adversarial attack approaches to speaker identification either need high computational cost or are not very effective, to our knowledge.
Exploring Effective Distillation of Self-Supervised Speech Models for Automatic Speech Recognition
Recent years have witnessed great strides in self-supervised learning (SSL) on the speech processing.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Multilingual Zero Resource Speech Recognition Base on Self-Supervise Pre-Trained Acoustic Models
Labeled audio data is insufficient to build satisfying speech recognition systems for most of the languages in the world.
Summary on the ISCSLP 2022 Chinese-English Code-Switching ASR Challenge
Code-switching automatic speech recognition becomes one of the most challenging and the most valuable scenarios of automatic speech recognition, due to the code-switching phenomenon between multilingual language and the frequent occurrence of code-switching phenomenon in daily life.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
The THUEE System Description for the IARPA OpenASR21 Challenge
For the Constrained training condition, we construct our basic ASR system based on the standard hybrid architecture.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
BERT-LID: Leveraging BERT to Improve Spoken Language Identification
It has a profound impact on the multilingual interoperability of an intelligent speech system.
Full Attention Bidirectional Deep Learning Structure for Single Channel Speech Enhancement
As the cornerstone of other important technologies, such as speech recognition and speech synthesis, speech enhancement is a critical area in audio signal processing.
AdaSpeech 3: Adaptive Text to Speech for Spontaneous Style
While recent text to speech (TTS) models perform very well in synthesizing reading-style (e. g., audiobook) speech, it is still challenging to synthesize spontaneous-style speech (e. g., podcast or conversation), mainly because of two reasons: 1) the lack of training data for spontaneous speech; 2) the difficulty in modeling the filled pauses (um and uh) and diverse rhythms in spontaneous speech.
DeepRapper: Neural Rap Generation with Rhyme and Rhythm Modeling
In this paper, we develop DeepRapper, a Transformer-based rap generation system that can model both rhymes and rhythms.
GigaSpeech: An Evolving, Multi-domain ASR Corpus with 10,000 Hours of Transcribed Audio
This paper introduces GigaSpeech, an evolving, multi-domain English speech recognition corpus with 10, 000 hours of high quality labeled audio suitable for supervised training, and 40, 000 hours of total audio suitable for semi-supervised and unsupervised training.
Ranked #1 on
Speech Recognition
on GigaSpeech
THUEE system description for NIST 2019 SRE CTS Challenge
This paper describes the systems submitted by the department of electronic engineering, institute of microelectronics of Tsinghua university and TsingMicro Co. Ltd. (THUEE) to the NIST 2019 speaker recognition evaluation CTS challenge.
SAM-GCNN: A Gated Convolutional Neural Network with Segment-Level Attention Mechanism for Home Activity Monitoring
To tackle this task, we propose a gated convolutional neural network with segment-level attention mechanism (SAM-GCNN).
