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Found 18 papers, 9 papers with code
Bridging the Modality Gap: Softly Discretizing Audio Representation for LLM-based Automatic Speech Recognition
One challenge of integrating speech input with large language models (LLMs) stems from the discrepancy between the continuous nature of audio data and the discrete token-based paradigm of LLMs.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Autoregressive Meta-Actions for Unified Controllable Trajectory Generation
Controllable trajectory generation guided by high-level semantic decisions, termed meta-actions, is crucial for autonomous driving systems.
DRoPE: Directional Rotary Position Embedding for Efficient Agent Interaction Modeling
We theoretically analyze DRoPE's correctness and efficiency, demonstrating its capability to simultaneously optimize trajectory generation accuracy, time complexity, and space complexity.
UniScene: Unified Occupancy-centric Driving Scene Generation
UniScene employs a progressive generation process that decomposes the complex task of scene generation into two hierarchical steps: (a) first generating semantic occupancy from a customized scene layout as a meta scene representation rich in both semantic and geometric information, and then (b) conditioned on occupancy, generating video and LiDAR data, respectively, with two novel transfer strategies of Gaussian-based Joint Rendering and Prior-guided Sparse Modeling.
Audiobox TTA-RAG: Improving Zero-Shot and Few-Shot Text-To-Audio with Retrieval-Augmented Generation
This work focuses on improving Text-To-Audio (TTA) generation on zero-shot and few-shot settings (i. e. generating unseen or uncommon audio events).
MCTrack: A Unified 3D Multi-Object Tracking Framework for Autonomous Driving
This paper introduces MCTrack, a new 3D multi-object tracking method that achieves state-of-the-art (SOTA) performance across KITTI, nuScenes, and Waymo datasets.
DiariST: Streaming Speech Translation with Speaker Diarization
End-to-end speech translation (ST) for conversation recordings involves several under-explored challenges such as speaker diarization (SD) without accurate word time stamps and handling of overlapping speech in a streaming fashion.
What Can an Accent Identifier Learn? Probing Phonetic and Prosodic Information in a Wav2vec2-based Accent Identification Model
This study is focused on understanding and quantifying the change in phoneme and prosody information encoded in the Self-Supervised Learning (SSL) model, brought by an accent identification (AID) fine-tuning task.
Learning ASR pathways: A sparse multilingual ASR model
Neural network pruning compresses automatic speech recognition (ASR) models effectively.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
Improving Mispronunciation Detection with Wav2vec2-based Momentum Pseudo-Labeling for Accentedness and Intelligibility Assessment
We show that fine-tuning with pseudo labels achieves a 5. 35% phoneme error rate reduction and 2. 48% MDD F1 score improvement over a labeled-samples-only fine-tuning baseline.
InverseMV: Composing Piano Scores with a Convolutional Video-Music Transformer
We conduct experiments with human evaluation on VMT, SeqSeq model (our baseline), and the original piano version soundtrack.
Towards Lifelong Learning of Multilingual Text-To-Speech Synthesis
This work presents a lifelong learning approach to train a multilingual Text-To-Speech (TTS) system, where each language was seen as an individual task and was learned sequentially and continually.
EventPlus: A Temporal Event Understanding Pipeline
We present EventPlus, a temporal event understanding pipeline that integrates various state-of-the-art event understanding components including event trigger and type detection, event argument detection, event duration and temporal relation extraction.
Biomedical Event Extraction with Hierarchical Knowledge Graphs
To better recognize the trigger words, each sentence is first grounded to a sentence graph based on a jointly modeled hierarchical knowledge graph from UMLS.
Ranked #2 on
Event Extraction
on GENIA
Headword-Oriented Entity Linking: A Special Entity Linking Task with Dataset and Baseline
In this paper, we design headword-oriented entity linking (HEL), a specialized entity linking problem in which only the headwords of the entities are to be linked to knowledge bases; mention scopes of the entities do not need to be identified in the problem setting.
Deep Structured Neural Network for Event Temporal Relation Extraction
We propose a novel deep structured learning framework for event temporal relation extraction.
Spoken Language Intent Detection using Confusion2Vec
In this paper, we address the spoken language intent detection under noisy conditions imposed by automatic speech recognition (ASR) systems.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
Deep Hybrid Scattering Image Learning
A well-trained deep neural network is shown to gain capability of simultaneously restoring two kinds of images, which are completely destroyed by two distinct scattering medias respectively.
