Text based user comments as a signal for automatic language identification of online videos
- Publication type
- C1
- Publication status
- Published
- Authors
- Doğruöz, A.S., Ponomareva, N., Girgin, S., Jain, R., & Oehler, C.
- Series
- ICMI'17 : Proceedings of the 19th ACM International Conference on Multimodal Interaction
- Pagination
- 374-378
- Publisher
- Association for Computing Machinery (ACM)
- Conference
- ICMI '17: International Conference on Multimodal Interaction (Glasgow, UK)
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- (.pdf)
- View in Biblio
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Abstract
Identifying the audio language of online videos is crucial for industrial multi-media applications. Automatic speech recognition systems can potentially detect the language of the audio. However, such systems are not available for all languages. Moreover, background noise, music and multi-party conversations make audio language identification hard. Instead, we utilize text based user comments as a new signal to identify audio language of YouTube videos. First, we detect the language of the text based comments. Augmenting this information with video meta-data features, we predict the language of the videos with an accuracy of 97% on a set of publicly available videos. The subject matter discussed in this research is patent pending.