Search Results for author:
Found 13 papers, 4 papers with code
FunAudioLLM: Voice Understanding and Generation Foundation Models for Natural Interaction Between Humans and LLMs
This report introduces FunAudioLLM, a model family designed to enhance natural voice interactions between humans and large language models (LLMs).
Towards a Client-Centered Assessment of LLM Therapists by Client Simulation
To this end, we adopt LLMs to simulate clients and propose ClientCAST, a client-centered approach to assessing LLM therapists by client simulation.
Text-Only Domain Adaptation for End-to-End Speech Recognition through Down-Sampling Acoustic Representation
Mapping two modalities, speech and text, into a shared representation space, is a research topic of using text-only data to improve end-to-end automatic speech recognition (ASR) performance in new domains.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
SememeASR: Boosting Performance of End-to-End Speech Recognition against Domain and Long-Tailed Data Shift with Sememe Semantic Knowledge
Recently, excellent progress has been made in speech recognition.
Improving Mandarin Prosodic Structure Prediction with Multi-level Contextual Information
For text-to-speech (TTS) synthesis, prosodic structure prediction (PSP) plays an important role in producing natural and intelligible speech.
Towards Cross-speaker Reading Style Transfer on Audiobook Dataset
This paper aims to introduce a chunk-wise multi-scale cross-speaker style model to capture both the global genre and the local prosody in audiobook speeches.
An End-to-end Chinese Text Normalization Model based on Rule-guided Flat-Lattice Transformer
Inspired by Flat-LAttice Transformer (FLAT), we propose an end-to-end Chinese text normalization model, which accepts Chinese characters as direct input and integrates expert knowledge contained in rules into the neural network, both contribute to the superior performance of proposed model for the text normalization task.
A Character-level Span-based Model for Mandarin Prosodic Structure Prediction
In this paper, we propose a span-based Mandarin prosodic structure prediction model to obtain an optimal prosodic structure tree, which can be converted to corresponding prosodic label sequence.
Disentangleing Content and Fine-grained Prosody Information via Hybrid ASR Bottleneck Features for Voice Conversion
In this paper, we proposed an any-to-one VC method using hybrid bottleneck features extracted from CTC-BNFs and CE-BNFs to complement each other advantages.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
Enhancing Word-Level Semantic Representation via Dependency Structure for Expressive Text-to-Speech Synthesis
Exploiting rich linguistic information in raw text is crucial for expressive text-to-speech (TTS).
Towards Multi-Scale Style Control for Expressive Speech Synthesis
This paper introduces a multi-scale speech style modeling method for end-to-end expressive speech synthesis.
Syntactic representation learning for neural network based TTS with syntactic parse tree traversal
Meanwhile, nuclear-norm maximization loss is introduced to enhance the discriminability and diversity of the embeddings of constituent labels.
CED: Credible Early Detection of Social Media Rumors
By regarding all reposts to a rumor candidate as a sequence, the proposed model will seek an early point-in-time for making a credible prediction.
Social and Information Networks
