SPEECH & AUDIO
Generative Pre-training for Speech with Flow Matching
March 05, 2024
Abstract
Generative models have gained more and more attention in recent years for their remarkable success in tasks that required estimating and sampling data distribution to generate high-fidelity synthetic data. In speech, text-to-speech synthesis and neural vocoder are good examples here generative models have shined. While generative models have been applied to different applications in speech, there exists no general-purpose generative model that models speech directly. In this work, we take a step toward this direction by showing a single pre-trained generative model can be adapted to different downstream tasks with strong performance. Specificall, we pre-trained a generative model, named SpeechFlow, on 60k hours of untranscribed speech with Flow Matching and masked conditions. Experiment results show the pre-trained generative model can be fine-tuned with task-specific data to match or surpass existing expert models on speech enhancement, separation, and synthesis. Our work suggested a foundational model for generation tasks in speech can be built with generative pre-training.
AUTHORS
Publisher
ICLR
Research Topics
Related Publications
November 04, 2026
SPEECH & AUDIO
GSLM2: Multi-Stream Speech Representation Learning and Generative Spoken Language Modeling
Yosuke Higuchi, Tom Fizycki, Mahi Luthra, Charles-Éric Saint-James, Azeez Syed, Angel Villar Corrales, Mido Assran, Nicolas Ballas, Jiayi Shen, Dongyan Lin, Phillip Rust, Surya Parimi, Vanessa Stark, Alexandre Allauzen, Balázs Kegl, Juan Pino, Emmanuel Dupoux
November 04, 2026
September 06, 2026
SPEECH & AUDIO
Alignment-Free Text-Audiobox for Voice Dubbing and Full-Duplex Dialogue Synthesis
Min-Jae Hwang, Sho Inoue, Bokai Yu, David Kant, Dongmin Hyun, Dorian Desblancs, Gregory Antonovsky, Oleg Repin, Zehai Tu, Juan Pino, Wei-Ning Hsu
September 06, 2026
May 12, 2026
HUMAN & MACHINE INTELLIGENCE
RESEARCH
NeuralSet: A High-Performing Python Package for Neuro-AI
Jean Remi King, Corentin Bel, Linnea Evanson, Julien Gadonneix, Sophia Houhamdi, Jarod Levy, Josephine Raugel, Andrea Santos Revilla, Mingfang (Lucy) Zhang, Julie Bonnaire, Charlotte Caucheteux, Alexandre Défossez, Théo Desbordes, Pablo Diego-Simón, Shubh Khanna, Juliette Millet, Pierre Orhan, Saarang Panchavati, Antoine Ratouchniak, Alexis Thual, Teon Brooks, Katelyn Begany, Yohann Benchetrit, Marlene Careil, Hubert Jacob Banville, Stéphane d'Ascoli, Simon Dahan, Jérémy Rapin
May 12, 2026
March 17, 2026
RESEARCH
SPEECH & AUDIO
Omnilingual SONAR: Cross-Lingual and Cross-Modal Sentence Embeddings Bridging Massively Multilingual Text and Speech
Omnilingual SONAR Team, João Maria Janeiro, Pere Lluís Huguet Cabot, Ioannis Tsiamas, Yen Meng, Vivek Iyer, Guillem Ramirez, Loic Barrault, Belen Alastruey, Xiang Tony Cao, Yu-An Chung, Marta R. Costa-jussa, David Dale, Kevin Heffernan, Jaehyeong Jo, Artyom Kozhevnikov, Alexandre Mourachko, Christophe Ropers, Holger Schwenk, Paul-Ambroise Duquenne
March 17, 2026
Help Us Pioneer The Future of AI
We share our open source frameworks, tools, libraries, and models for everything from research exploration to large-scale production deployment.
Meta © 2026
