Audio

Learning Speech Representations with Flexible Hidden Feature Dimensions
Non-parallel many-to-many voice conversion is a kind of style transfer task in speech. Recently, AutoVC has been applied in this field …
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Learning Speech Representations with Flexible Hidden Feature Dimensions
QI-TTS: Questioning Intonation Control for Emotional Speech Synthesis
Recent expressive text to speech (TTS) models focus on synthesizing emotional speech, but some fine-grained styles such as intonation …
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QI-TTS: Questioning Intonation Control for Emotional Speech Synthesis
VQ-CL: Learning Disentangled Speech Representations with Contrastive Learning and Vector Quantization
Voice Conversion(VC) refers to converting the voice char- acteristics of audio to another one as it is said by other people. Recently, …
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VQ-CL: Learning Disentangled Speech Representations with Contrastive Learning and Vector Quantization
Feature-Rich Audio Model Inversion for Data-Free Knowledge Distillation Towards General Sound Classification
Data-Free Knowledge Distillation (DFKD) has recently attracted growing attention in the academic community, especially with major …
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Feature-Rich Audio Model Inversion for Data-Free Knowledge Distillation Towards General Sound Classification
Melody Generation from Lyrics with Local Interpretability
Melody generation aims to learn the distribution of real melodies to generate new melodies conditioned on lyrics, which has been a very …
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Melody Generation from Lyrics with Local Interpretability
SVLDL: Improved Speaker Age Estimation Using Selective Variance Label Distribution Learning
Estimating age from a single speech is a classic and challenging topic. Although Label Distribution Learning (LDL) can represent …
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SVLDL: Improved Speaker Age Estimation Using Selective Variance Label Distribution Learning
Adapitch: Adaption Multi-Speaker Text-to-Speech Conditioned on Pitch Disentangling with Untranscribed Data
In this paper, we proposed Adapitch, a multi-speaker TTS method that makes adaptation of the supervised module with untranscribed data. …
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Adapitch: Adaption Multi-Speaker Text-to-Speech Conditioned on Pitch Disentangling with Untranscribed Data
Improving Speech Representation Learning via Speech-level and Phoneme-level Masking Approach
Recovering the masked speech frames is widely applied in speech representation learning. However, most of these models use random …
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Improving Speech Representation Learning via Speech-level and Phoneme-level Masking Approach
Linguistic-Enhanced Transformer with CTC Embedding for Speech Recognition
The recent emergence of joint CTC-Attention model shows significant improvement in automatic speech recognition (ASR). The improvement …
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Linguistic-Enhanced Transformer with CTC Embedding for Speech Recognition
MetaSpeech: Speech Effects Switch Along with Environment for Metaverse
Metaverse expands the physical world to a new dimension, and the physical environment and Metaverse environment can be directly …
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MetaSpeech: Speech Effects Switch Along with Environment for Metaverse