13 papers
Scaling Open Discrete Audio Foundation Models with Interleaved Semantic, Acoustic, and Text Tokens
Potsawee Manakul, Woody Haosheng Gan, Martijn Bartelds +3
Current audio language models are predominantly text-first, either extending pre-trained text LLM backbones or relying on semantic-only audio tokens, limiting general audio modelin…
FinCoT: Grounding Chain-of-Thought in Expert Financial Reasoning
Natapong Nitarach, Warit Sirichotedumrong, Panop Pitchayarthorn +3
This paper presents FinCoT, a structured chain-of-thought (CoT) prompting framework that embeds domain-specific expert financial reasoning blueprints to guide large language models…
Extending Audio Context for Long-Form Understanding in Large Audio-Language Models
Yuatyong Chaichana, Pittawat Taveekitworachai, Warit Sirichotedumrong +2
Large Audio-Language Models (LALMs) are often constrained by short audio context windows, even when their text backbones support long contexts, limiting long-form audio understandi…
Typhoon ASR Real-time: FastConformer-Transducer for Thai Automatic Speech Recognition
Warit Sirichotedumrong, Adisai Na-Thalang, Potsawee Manakul +3
Large encoder-decoder models like Whisper achieve strong offline transcription but remain impractical for streaming applications due to high latency. However, due to the accessibil…
Prior Prompt Engineering for Reinforcement Fine-Tuning
Pittawat Taveekitworachai, Potsawee Manakul, Sarana Nutanong +1
This paper investigates prior prompt engineering (pPE) in the context of reinforcement fine-tuning (RFT), where language models (LMs) are incentivized to exhibit behaviors that max…
AudioJudge: Understanding What Works in Large Audio Model Based Speech Evaluation
Potsawee Manakul, Woody Haosheng Gan, Michael J. Ryan +5
Current speech evaluation suffers from two critical limitations: the need and difficulty of designing specialized systems targeting individual audio characteristics, and poor corre…