Search Results for author:
Found 10 papers, 7 papers with code
Upcycling Large Language Models into Mixture of Experts
Upcycling pre-trained dense language models into sparse mixture-of-experts (MoE) models is an efficient approach to increase the model capacity of already trained models.
LeanDojo: Theorem Proving with Retrieval-Augmented Language Models
Using this data, we develop ReProver (Retrieval-Augmented Prover): an LLM-based prover augmented with retrieval for selecting premises from a vast math library.
Context Generation Improves Open Domain Question Answering
Prior work on closed-book QA either directly finetunes or prompts a pretrained language model (LM) to leverage the stored knowledge.
Multi-Stage Prompting for Knowledgeable Dialogue Generation
We propose a multi-stage prompting approach to generate knowledgeable responses from a single pretrained LM.
Flowtron: an Autoregressive Flow-based Generative Network for Text-to-Speech Synthesis
In this paper we propose Flowtron: an autoregressive flow-based generative network for text-to-speech synthesis with control over speech variation and style transfer.
Ranked #1 on
Text-To-Speech Synthesis
on LJSpeech
(Pleasantness MOS metric, using extra
training data)
Mellotron: Multispeaker expressive voice synthesis by conditioning on rhythm, pitch and global style tokens
Mellotron is a multispeaker voice synthesis model based on Tacotron 2 GST that can make a voice emote and sing without emotive or singing training data.
WaveGlow: A Flow-based Generative Network for Speech Synthesis
In this paper we propose WaveGlow: a flow-based network capable of generating high quality speech from mel-spectrograms.
Ranked #12 on
Speech Synthesis
on LibriTTS
Convolutional Recurrent Neural Networks for Small-Footprint Keyword Spotting
Keyword spotting (KWS) constitutes a major component of human-technology interfaces.
Deep Speech 2: End-to-End Speech Recognition in English and Mandarin
We show that an end-to-end deep learning approach can be used to recognize either English or Mandarin Chinese speech--two vastly different languages.
Deep Speech: Scaling up end-to-end speech recognition
We present a state-of-the-art speech recognition system developed using end-to-end deep learning.
