Sped_up_audios_wtimestamps (Exclusive Deal)

: This 2024 paper improves timestamp precision for OpenAI's Whisper model. It addresses "unsharp" timestamps caused by pauses or rapid speech by adjusting the model's tokenizer and using cross-attention scores for alignment.

: A 2025 paper that introduces a data-driven approach using the Canary model. It uses a <|timestamp|> token to predict start and end times for words with high precision (80–90%), even as audio characteristics change. sped_up_audios_wtimestamps

WhisperX: Automatic Speech Recognition with Word ... - GitHub : This 2024 paper improves timestamp precision for

: This paper explores the effectiveness of combining transcripts with pitch-normalized, time-compressed speech. It specifically looks at how speed impacts user comprehension and the accuracy of machine-generated text alignments. It uses a token to predict start and

While there isn't a single famous paper with that exact title, several research papers specifically address the challenges of generating accurate for time-compressed (sped up) audio, often using techniques like SOLAFS or modern AI alignment. Key Research Papers