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Spoken Language Understanding
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논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Factorized RVQ-GAN For Disentangled Speech Tokenization
MMSU: A Massive Multi-task Spoken Language Understanding and Reasoning Benchmark
ALAS: Measuring Latent Speech-Text Alignment For Spoken Language Understanding In Multimodal LLMs
"KAN you hear me?" Exploring Kolmogorov-Arnold Networks for Spoken Language Understanding
Audio Jailbreak Attacks: Exposing Vulnerabilities in SpeechGPT in a White-Box Framework
Exploring the Effect of Segmentation and Vocabulary Size on Speech Tokenization for Speech Language Models
"Alexa, can you forget me?" Machine Unlearning Benchmark in Spoken Language Understanding
Impact of Frame Rates on Speech Tokenizer: A Case Study on Mandarin and English
QUADS: QUAntized Distillation Framework for Efficient Speech Language Understanding
Spoken Language Understanding on Unseen Tasks With In-Context Learning
LiveLongBench: Tackling Long-Context Understanding for Spoken Texts from Live Streams
TASTE: Text-Aligned Speech Tokenization and Embedding for Spoken Language Modeling
UniWav: Towards Unified Pre-training for Speech Representation Learning and Generation
Measuring the Effect of Transcription Noise on Downstream Language Understanding Tasks
Recent Advances in Discrete Speech Tokens: A Review
On the use of Performer and Agent Attention for Spoken Language Identification
Joint Automatic Speech Recognition And Structure Learning For Better Speech Understanding
Fleurs-SLU: A Massively Multilingual Benchmark for Spoken Language Understanding
Improving Transducer-Based Spoken Language Understanding with Self-Conditioned CTC and Knowledge Transfer
An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving
RETQA: A Large-Scale Open-Domain Tabular Question Answering Dataset for Real Estate Sector
BEST-STD: Bidirectional Mamba-Enhanced Speech Tokenization for Spoken Term Detection
DC-Spin: A Speaker-invariant Speech Tokenizer for Spoken Language Models
A Survey on Speech Large Language Models
Interventional Speech Noise Injection for ASR Generalizable Spoken Language Understanding
DM-Codec: Distilling Multimodal Representations for Speech Tokenization
Sylber: Syllabic Embedding Representation of Speech from Raw Audio
SyllableLM: Learning Coarse Semantic Units for Speech Language Models
AfriHuBERT: A self-supervised speech representation model for African languages
Improving Multilingual ASR in the Wild Using Simple N-best Re-ranking
Speech Recognition Rescoring with Large Speech-Text Foundation Models
MultiMed: Multilingual Medical Speech Recognition via Attention Encoder Decoder
Increasing faithfulness in human-human dialog summarization with Spoken Language Understanding tasks
Self-Supervised Syllable Discovery Based on Speaker-Disentangled HuBERT
Clean Label Attacks against SLU Systems
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.