Search Results for author:
Found 11 papers, 4 papers with code
SA-WavLM: Speaker-Aware Self-Supervised Pre-training for Mixture Speech
Specifically, SA-WavLM follows an "extract-merge-predict" pipeline in which the representations of each speaker in the input mixture are first extracted individually and then merged before the final prediction.
Prompt-driven Target Speech Diarization
We introduce a novel task named `target speech diarization', which seeks to determine `when target event occurred' within an audio signal.
DisCover: Disentangled Music Representation Learning for Cover Song Identification
We analyze the CSI task in a disentanglement view with the causal graph technique, and identify the intra-version and inter-version effects biasing the invariant learning.
M4Singer: a Multi-Style, Multi-Singer and Musical Score Provided Mandarin Singing Corpus
The lack of publicly available high-quality and accurately labeled datasets has long been a major bottleneck for singing voice synthesis (SVS).
CorrectSpeech: A Fully Automated System for Speech Correction and Accent Reduction
This study propose a fully automated system for speech correction and accent reduction.
Reducing language context confusion for end-to-end code-switching automatic speech recognition
We propose a language-related attention mechanism to reduce multilingual context confusion for the E2E code-switching ASR model based on the Equivalence Constraint (EC) Theory.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
CoCA-MDD: A Coupled Cross-Attention based Framework for Streaming Mispronunciation Detection and Diagnosis
We utilize conv-transformer structure to encode input speech in a streaming manner.
EditSpeech: A Text Based Speech Editing System Using Partial Inference and Bidirectional Fusion
This paper presents the design, implementation and evaluation of a speech editing system, named EditSpeech, which allows a user to perform deletion, insertion and replacement of words in a given speech utterance, without causing audible degradation in speech quality and naturalness.
VQMIVC: Vector Quantization and Mutual Information-Based Unsupervised Speech Representation Disentanglement for One-shot Voice Conversion
One-shot voice conversion (VC), which performs conversion across arbitrary speakers with only a single target-speaker utterance for reference, can be effectively achieved by speech representation disentanglement.
Unsupervised Domain Adaptation for Dysarthric Speech Detection via Domain Adversarial Training and Mutual Information Minimization
Such systems are particularly susceptible to domain mismatch where the training and testing data come from the source and target domains respectively, but the two domains may differ in terms of speech stimuli, disease etiology, etc.
Unified Mandarin TTS Front-end Based on Distilled BERT Model
The front-end module in a typical Mandarin text-to-speech system (TTS) is composed of a long pipeline of text processing components, which requires extensive efforts to build and is prone to large accumulative model size and cascade errors.
