1 citations · 2 across the 7 of their papers we have counts for
7 papers
Using LLMs for Late Multimodal Sensor Fusion for Activity Recognition
Ilker Demirel, Karan Thakkar, Benjamin Elizalde +7
Sensor data streams provide valuable information around activities and context for downstream applications, though integrating complementary information can be challenging. We show…
Discrete Audio Tokens: More Than a Survey!
Pooneh Mousavi, Gallil Maimon, Adel Moumen +18
Discrete audio tokens are compact representations that aim to preserve perceptual quality, phonetic content, and speaker characteristics while enabling efficient storage and infere…
Audio Entailment: Assessing Deductive Reasoning for Audio Understanding
Soham Deshmukh, Shuo Han, Hazim Bukhari +4
Recent literature uses language to build foundation models for audio. These Audio-Language Models (ALMs) are trained on a vast number of audio-text pairs and show remarkable perfor…
PAM: Prompting Audio-Language Models for Audio Quality Assessment
Soham Deshmukh, Dareen Alharthi, Benjamin Elizalde +5
While audio quality is a key performance metric for various audio processing tasks, including generative modeling, its objective measurement remains a challenge. Audio-Language Mod…
NOTSOFAR-1 Challenge: New Datasets, Baseline, and Tasks for Distant Meeting Transcription
Alon Vinnikov, Amir Ivry, Aviv Hurvitz +16
We introduce the first Natural Office Talkers in Settings of Far-field Audio Recordings (``NOTSOFAR-1'') Challenge alongside datasets and baseline system. The challenge focuses on…
Prompting Audios Using Acoustic Properties For Emotion Representation
Hira Dhamyal, Benjamin Elizalde, Soham Deshmukh +3
Emotions lie on a continuum, but current models treat emotions as a finite valued discrete variable. This representation does not capture the diversity in the expression of emotion…
Natural Language Supervision for General-Purpose Audio Representations
Benjamin Elizalde, Soham Deshmukh, Huaming Wang
Audio-Language models jointly learn multimodal text and audio representations that enable Zero-Shot inference. Models rely on the encoders to create powerful representations of the…