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Minghui Fang

15 accepted papers

2025

CART: A Generative Cross-Modal Retrieval Framework With Coarse-To-Fine Semantic Modeling

ACL 2025long

Cross-modal retrieval aims to search for instances, which are semantically related to the query through the interaction of different modal data. Traditional solutions utilize a single-tower or dual-tower framework to explicitly compute the score between queries and candidates, which is challenged by…

Cited by 0SourcePDFScholar
2025

ControlSpeech: Towards Simultaneous and Independent Zero-shot Speaker Cloning and Zero-shot Language Style Control

ACL 2025long

In this paper, we present ControlSpeech, a text-to-speech (TTS) system capable of fully cloning the speaker’s voice and enabling arbitrary control and adjustment of speaking style. Prior zero-shot TTS models only mimic the speaker’s voice without further control and adjustment capabilities while pri…

2025

Enhancing Expressive Voice Conversion with Discrete Pitch-Conditioned Flow Matching Model

ICASSP 2025accepted

This paper introduces PFlow-VC, a conditional flow matching voice conversion model that leverages fine-grained discrete pitch tokens and target speaker prompt information for expressive voice conversion (VC). Previous VC works primarily focus on speaker conversion, with further exploration needed in…

Cited by 11SourceScholar
2025

Enhancing Multimodal Unified Representations for Cross Modal Generalization

ACL 2025finding

To enhance the interpretability of multimodal unified representations, many studies have focused on discrete unified representations. These efforts typically start with contrastive learning and gradually extend to the disentanglement of modal information, achieving solid multimodal discrete unified…

2025

Language-Codec: Bridging Discrete Codec Representations and Speech Language Models

ACL 2025long

In recent years, large language models have achieved significant success in generative tasks (e.g., speech cloning and audio generation) related to speech, audio, music, and other signal domains. A crucial element of these models is the discrete acoustic codecs, which serve as an intermediate repres…

2025

Mitigating Hallucinations in LM-Based TTS Models via Distribution Alignment Using GFlowNets

EMNLP 2025

Language Model (LM)-based Text-to-Speech (TTS) systems often generate hallucinated speech that deviates from input text. Existing mitigation strategies either demand excessive training resources or introduce significant inference latency. In this paper, we propose GFlOwNet-guided distribution Alignm

2025

OmniSep: Unified Omni-Modality Sound Separation with Query-Mixup

ICLR 2025poster

Query-based sound separation (QSS) effectively isolate sound signals that match the content of a given query, enhancing the understanding of audio data. However, most existing QSS methods rely on a single modality for separation, lacking the ability to fully leverage homologous but heterogeneous inf…

2025

Rhythm Controllable and Efficient Zero-Shot Voice Conversion via Shortcut Flow Matching

ACL 2025long

Zero-Shot Voice Conversion (VC) aims to transform the source speaker’s timbre into an arbitrary unseen one while retaining speech content. Most prior work focuses on preserving the source’s prosody, while fine-grained timbre information may leak through prosody, and transferring target prosody to sy…

2025

Speech Watermarking with Discrete Intermediate Representations

AAAI 2025technical

Speech watermarking techniques can proactively mitigate the potential harmful consequences of instant voice cloning techniques. These techniques involve the insertion of signals into speech that are imperceptible to humans but can be detected by algorithms. Previous approaches typically embed waterm…

Cited by 1SourcePDFScholar
2025

VoxpopuliTTS: a large-scale multilingual TTS corpus for zero-shot speech generation

COLING 2025main

In recent years, speech generation fields have achieved significant advancements, primarily due to improvements in large TTS (text-to-speech) systems and scalable TTS datasets. However, there is still a lack of large-scale multilingual TTS datasets, which limits the development of cross-language and…

Cited by 0SourcePDFScholar
2025

WavTokenizer: an Efficient Acoustic Discrete Codec Tokenizer for Audio Language Modeling

ICLR 2025poster

Language models have been effectively applied to modeling natural signals, such as images, video, speech, and audio. A crucial component of these models is the codec tokenizer, which compresses high-dimensional natural signals into lower-dimensional discrete tokens. In this paper, we introduce WavTo…

2025

Zero-resource Hallucination Detection for Text Generation via Graph-based Contextual Knowledge Triples Modeling

AAAI 2025technical

LLMs obtain remarkable performance but suffer from hallucinations. Most research on detecting hallucination focuses on questions with short and concrete correct answers that are easy to check faithfulness. Hallucination detections for text generation with open-ended answers are more hard. Some resea…

2024

AudioVSR: Enhancing Video Speech Recognition with Audio Data

EMNLP 2024main

Visual Speech Recognition (VSR) aims to predict spoken content by analyzing lip movements in videos. Recently reported state-of-the-art results in VSR often rely on increasingly large amounts of video data, while the publicly available transcribed video datasets are insufficient compared to the audi…

Cited by 1SourcePDFScholar
2024

MoMu-Diffusion: On Learning Long-Term Motion-Music Synchronization and Correspondence

NeurIPS 2024poster

Motion-to-music and music-to-motion have been studied separately, each attracting substantial research interest within their respective domains. The interaction between human motion and music is a reflection of advanced human intelligence, and establishing a unified relationship between them is part…

2024

TextrolSpeech: A Text Style Control Speech Corpus with Codec Language Text-to-Speech Models

ICASSP 2024accepted

Recently, there has been a growing interest in the field of controllable Text-to-Speech (TTS). While previous studies have relied on users providing specific style factor values based on acoustic knowledge or selecting reference speeches that meet certain requirements, generating speech solely from…

Cited by 0SourceScholar