Query-by-Example Spoken Term Detection ALBAYZIN 2012 evaluation: overview, systems, results, and discussion
| Autor: | Javier Tejedor, Doroteo Torre Toledano, Lluís F. Hurtado, José Colás, Antonio Miguel, Amparo Varona, Xavier Anguera |
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| Přispěvatelé: | UAM. Departamento de Tecnología Electrónica y de las Comunicaciones, Análisis y Tratamiento de Voz y Señales Biométricas (ING EPS-002), Laboratorio de Tecnología Hombre-Computador (ING EPS-010) |
| Jazyk: | angličtina |
| Rok vydání: | 2013 |
| Předmět: |
Dynamic time warping
Acoustics and Ultrasonics spoken term detection Computer science Speech recognition Context (language use) computer.software_genre Task (project management) ACOUSTICS query-by-example Query by Example international evaluation Electrical and Electronic Engineering ELECTRICAL AND ELECTRONIC ENGINEERING computer.programming_language Telecomunicaciones search on spontaneous speech business.industry Speech corpus Term (time) Keyword spotting Artificial intelligence Transcription (software) business LENGUAJES Y SISTEMAS INFORMATICOS computer Natural language processing |
| Zdroj: | Addi. Archivo Digital para la Docencia y la Investigación instname Biblos-e Archivo. Repositorio Institucional de la UAM Zaguán. Repositorio Digital de la Universidad de Zaragoza RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia |
| Popis: | The electronic version of this article is the complete one and can be found online at: http://asmp.eurasipjournals.com/content/2013/1/23 Query-by-Example Spoken Term Detection (QbE STD) aims at retrieving data from a speech data repository given an acoustic query containing the term of interest as input. Nowadays, it has been receiving much interest due to the high volume of information stored in audio or audiovisual format. QbE STD differs from automatic speech recognition (ASR) and keyword spotting (KWS)/spoken term detection (STD) since ASR is interested in all the terms/words that appear in the speech signal and KWS/STD relies on a textual transcription of the search term to retrieve the speech data. This paper presents the systems submitted to the ALBAYZIN 2012 QbE STD evaluation held as a part of ALBAYZIN 2012 evaluation campaign within the context of the IberSPEECH 2012 Conferencea. The evaluation consists of retrieving the speech files that contain the input queries, indicating their start and end timestamps within the appropriate speech file. Evaluation is conducted on a Spanish spontaneous speech database containing a set of talks from MAVIR workshopsb, which amount at about 7 h of speech in total. We present the database metric systems submitted along with all results and some discussion. Four different research groups took part in the evaluation. Evaluation results show the difficulty of this task and the limited performance indicates there is still a lot of room for improvement. The best result is achieved by a dynamic time warping-based search over Gaussian posteriorgrams/posterior phoneme probabilities. This paper also compares the systems aiming at establishing the best technique dealing with that difficult task and looking for defining promising directions for this relatively novel task. |
| Databáze: | OpenAIRE |
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