paper-with-me

홈 › Papers

Me, myself, and ire: Effects of automatic transcription quality on emotion, sarcasm, and personality detection

2021-04-01 · EACL (WASSA) 2021 4 · John Culnan, SeongJin Park, Meghavarshini Krishnaswamy, Rebecca Sharp

In deployment, systems that use speech as input must make use of automated transcriptions. Yet, typically when these systems are evaluated, gold transcriptions are assumed. We explicitly examine the impact of transcription errors on the downstream performance of a multi-modal system on three related tasks from three datasets: emotion, sarcasm, and personality detection. We include three separate transcription tools and show that while all automated transcriptions propagate errors that substantially impact downstream performance, the open-source tools fair worse than the paid tool, though not always straightforwardly, and word error rates do not correlate well with downstream performance. We further find that the inclusion of audio features partially mitigates transcription errors, but that a naive usage of a multi-task setup does not.

📄 PDF Abstract BibTeX

Code (0)

등록된 구현이 없습니다.

Similar Papers 제목 키워드 기반

Optimizing Computer-Assisted Transcription Quality with Iterative User Interfaces

2016-05-01 · LREC 2016 5 · Matthias Sperber, Graham Neubig, Satoshi Nakamura, Alex Waibel

Computer-assisted transcription promises high-quality speech transcription at reduced costs. This is achieved by limiting human effort to transcribing parts for which automatic transcription quality is insufficient. Our …

EmoAra: Emotion-Preserving English Speech Transcription and Cross-Lingual Translation with Arabic Text-to-Speech

2026-02-01 · Besher Hassan, Ibrahim Alsarraj, Musaab Hasan, Yousef Melhim 외 arxiv

This work presents EmoAra, an end-to-end emotion-preserving pipeline for cross-lingual spoken communication, motivated by banking customer service where emotional context affects service quality. EmoAra integrates Speech…

Speech Emotion RecognitionEmotion ClassificationMachine TranslationSpeech Recognition

Is Semi-Automatic Transcription Useful in Corpus Creation? Preliminary Considerations on the KIParla Corpus

2026-03-17 · Martina Simonotti, Ludovica Pannitto, Eleonora Zucchini, Silvia Ballarè 외 arxiv

This paper analyses the implementation of Automatic Speech Recognition (ASR) into the transcription workflow of the KIParla corpus, a resource of spoken Italian. Through a two-phase experiment, 11 expert and novice trans…

Speech Recognition

VioPTT: Violin Technique-Aware Transcription from Synthetic Data Augmentation

2025-09-28 · Ting-Kang Wang, Yueh-Po Peng, Li Su, Vincent K. M. Cheung arxiv

While automatic music transcription is well-established in music information retrieval, most models are limited to transcribing pitch and timing information from audio, and thus omit crucial expressive and instrument-spe…

Information RetrievalMusic TranscriptionData Augmentation

Towards Automatic Transcription of ILSE ― an Interdisciplinary Longitudinal Study of Adult Development and Aging

2016-05-01 · LREC 2016 5 · Jochen Weiner, Claudia Frankenberg, Dominic Telaar, Britta Wendelstein 외

The Interdisciplinary Longitudinal Study on Adult Development and Aging (ILSE) was created to facilitate the study of challenges posed by rapidly aging societies in developed countries such as Germany. ILSE contains over…

Automatic Speech RecognitionAutomatic Speech Recognition (ASR)speech-recognitionSpeech Recognition