261 citations · 426 across the 33 of their papers we have counts for
36 papers
HEAR: Real Voices, Real Bias: A Large-Scale Human-Recorded, Demographically Diverse Benchmark for Audio Language Models
Shen Yan, Duc Le, Irina-Elena Veliche
We introduce HEAR (Human-recorded Evaluation of Audio-LLM bias by Real speakers), a large-scale, ecologically valid benchmark comprising 87k real human audio samples from 843 demog…
MELD: Mel-Spectrogram-Based Speech Language Modeling with Discrete Latent Variables
Sung-Lin Yeh, Wei Zhou, Gil Keren +6
Recent speech language models rely on encoders that are optimized separately from autoregressive models. Since these encoders are unaware of the downstream objectives, the extracte…
Textless Streaming Speech-to-Speech Translation using Semantic Speech Tokens
Jinzheng Zhao, Niko Moritz, Egor Lakomkin +7
Cascaded speech-to-speech translation systems often suffer from the error accumulation problem and high latency, which is a result of cascaded modules whose inference delays accumu…
The Llama 3 Herd of Models
Aaron Grattafiori, Abhimanyu Dubey, Abhinav Jauhri +556
Modern artificial intelligence (AI) systems are powered by foundation models. This paper presents a new set of foundation models, called Llama 3. It is a herd of language models th…
IndicVoices: Towards building an Inclusive Multilingual Speech Dataset for Indian Languages
Tahir Javed, Janki Atul Nawale, Eldho Ittan George +18
We present INDICVOICES, a dataset of natural and spontaneous speech containing a total of 7348 hours of read (9%), extempore (74%) and conversational (17%) audio from 16237 speaker…
Seq2seq for Automatic Paraphasia Detection in Aphasic Speech
Matthew Perez, Duc Le, Amrit Romana +3
Paraphasias are speech errors that are often characteristic of aphasia and they represent an important signal in assessing disease severity and subtype. Traditionally, clinicians m…