- -

ALBAYZIN Query-by-example Spoken Term Detection 2016 evaluation

RiuNet: Repositorio Institucional de la Universidad Politécnica de Valencia

Compartir/Enviar a

Citas

Estadísticas

  • Estadisticas de Uso

ALBAYZIN Query-by-example Spoken Term Detection 2016 evaluation

Mostrar el registro sencillo del ítem

Ficheros en el ítem

Thumbnail
Nombre: Tejedor;Toledano; ...
Tamaño: 1.609Mb
Formato: PDF
Descripción: Versión editorial
Abrir
dc.contributor.author Tejedor, Javier es_ES
dc.contributor.author Toledano, Doroteo T. es_ES
dc.contributor.author Lopez-Otero, Paula es_ES
dc.contributor.author Docio-Fernandez, Laura es_ES
dc.contributor.author Proença, Jorge es_ES
dc.contributor.author Perdigão, Fernando es_ES
dc.contributor.author García-Granada, Fernando es_ES
dc.contributor.author Sanchís Arnal, Emilio es_ES
dc.contributor.author Pompili, Anna es_ES
dc.contributor.author Abad, Alberto es_ES
dc.date.accessioned 2020-06-09T03:31:45Z
dc.date.available 2020-06-09T03:31:45Z
dc.date.issued 2018 es_ES
dc.identifier.issn 1687-4722 es_ES
dc.identifier.uri http://hdl.handle.net/10251/145736
dc.description.abstract [EN] Query-by-example Spoken Term Detection (QbE STD) aims to retrieve data from a speech repository given an acoustic (spoken) query containing the term of interest as the input. This paper presents the systems submitted to the ALBAYZIN QbE STD 2016 Evaluation held as a part of the ALBAYZIN 2016 Evaluation Campaign at the IberSPEECH 2016 conference. Special attention was given to the evaluation design so that a thorough post-analysis of the main results could be carried out. Two different Spanish speech databases, which cover different acoustic and language domains, were used in the evaluation: the MAVIR database, which consists of a set of talks from workshops, and the EPIC database, which consists of a set of European Parliament sessions in Spanish. We present the evaluation design, both databases, the evaluation metric, the systems submitted to the evaluation, the results, and a thorough analysis and discussion. Four different research groups participated in the evaluation, and a total of eight template matching-based systems were submitted. We compare the systems submitted to the evaluation and make an in-depth analysis based on some properties of the spoken queries, such as query length, single-word/multi-word queries, and in-language/out-of-language queries. es_ES
dc.description.sponsorship This work was partially supported by Fundacao para a Ciencia e Tecnologia (FCT) under the projects UID/EEA/50008/2013 (pluriannual funding in the scope of the LETSREAD project) and UID/CEC/50021/2013, and Grant SFRH/BD/97187/2013. Jorge Proenca is supported by the SFRH/BD/97204/2013 FCT Grant. This work was also supported by the Galician Government ('Centro singular de investigacion de Galicia' accreditation 2016-2019 ED431G/01 and the research contract GRC2014/024 (Modalidade: Grupos de Referencia Competitiva 2014)), the European Regional Development Fund (ERDF), the projects "DSSL: Redes Profundas y Modelos de Subespacios para Deteccion y Seguimiento de Locutor, Idioma y Enfermedades Degenerativas a partir de la Voz" (TEC2015-68172-C2-1-P) and the TIN2015-64282-R funded by Ministerio de Economia y Competitividad in Spain, the Spanish Government through the project "TraceThem" (TEC2015-65345-P), and AtlantTIC ED431G/04. es_ES
dc.language Inglés es_ES
dc.publisher Springer (Biomed Central Ltd.) es_ES
dc.relation AtlantTIC/ED431G/04 es_ES
dc.relation.ispartof EURASIP Journal on Audio, Speech and Music Processing es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Query-by-example es_ES
dc.subject Spoken Term Detectio es_ES
dc.subject International evaluation es_ES
dc.subject Spanish,Search on spontaneous speech es_ES
dc.subject.classification LENGUAJES Y SISTEMAS INFORMATICOS es_ES
dc.title ALBAYZIN Query-by-example Spoken Term Detection 2016 evaluation es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1186/s13636-018-0125-9 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/Xunta de Galicia//ED431G%2F01/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/FCT/5876/147328/PT/Instituto de Telecomunicações/
dc.relation.projectID info:eu-repo/grantAgreement/Xunta de Galicia//GRC2014%2F024/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/FCT/5876/147282/PT/Instituto de Engenharia de Sistemas e Computadores, Investigação e Desenvolvimento em Lisboa/
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//TEC2015-68172-C2-1-P/ES/REDES PROFUNDAS Y MODELOS DE SUBESPACIOS PARA DETECCION Y SEGUIMIENTO DE LOCUTOR, IDIOMA Y ENFERMEDADES DEGENERATIVAS A PARTIR DE LA VOZ/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/FCT/SFRH/SFRH%2FBD%2F97204%2F2013/PT/
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//TEC2015-65345-P/ES/DETECCION MULTIMEDIA Y MULTILINGUE DE INFORMACION SOBRE PERSONAS/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/FCT/SFRH/SFRH%2FBD%2F97187%2F2013/PT/
dc.relation.projectID info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TIN2017-85854-C4-2-R/ES/AMIC-UPV: ANALISIS AFECTIVO DE INFORMACION MULTIMEDIA CON COMUNICACION INCLUSIVA Y NATURAL/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació es_ES
dc.description.bibliographicCitation Tejedor, J.; Toledano, DT.; Lopez-Otero, P.; Docio-Fernandez, L.; Proença, J.; Perdigão, F.; García-Granada, F.... (2018). ALBAYZIN Query-by-example Spoken Term Detection 2016 evaluation. EURASIP Journal on Audio, Speech and Music Processing. 1-25. https://doi.org/10.1186/s13636-018-0125-9 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1186/s13636-018-0125-9 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 25 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.relation.pasarela S\369385 es_ES
dc.contributor.funder Xunta de Galicia es_ES
dc.contributor.funder Agencia Estatal de Investigación es_ES
dc.contributor.funder Ministerio de Ciencia e Innovación es_ES
dc.contributor.funder Fundação para a Ciência e a Tecnologia, Portugal es_ES
dc.contributor.funder Atlantic Research Center for Information and Communication Technologies es_ES
dc.contributor.funder Ministerio de Economía y Competitividad es_ES
dc.description.references Jarina, R, Kuba, M, Gubka, R, Chmulik, M, Paralic, M (2013). UNIZA system for the spoken web search task at MediaEval 2013. In Proc. of MediaEval. Ruzica Piskac, New Haven, (pp. 791–792). es_ES
dc.description.references Ali, A, & Clements, MA (2013). Spoken web search using and ergodic hidden Markov model of speech. In Proc. of MediaEval. Ruzica Piskac, New Haven, (pp. 861–862). es_ES
dc.description.references Buzo, A, Cucu, H, Burileanu, C (2014). SpeeD@MediaEval 2014: Spoken term detection with robust multilingual phone recognition. In Proc. of MediaEval. Ruzica Piskac, New Haven, (pp. 721–722). es_ES
dc.description.references Caranica, A, Buzo, A, Cucu, H, Burileanu, C (2015). SpeeD@MediaEval 2015: Multilingual phone recognition approach to Query By Example STD. In Proc. of MediaEval. Ruzica Piskac, New Haven, (pp. 781–783). es_ES
dc.description.references Kesiraju, S, Mantena, G, Prahallad, K (2014). IIIT-H system for MediaEval 2014 QUESST. In Proc. of MediaEval. Ruzica Piskac, New Haven, (pp. 761–762). es_ES
dc.description.references Ma, M, & Rosenberg, A (2015). CUNY systems for the Query-by-Example search on speech task at MediaEval 2015. In Proc. of MediaEval. Ruzica Piskac, New Haven, (pp. 831–833). es_ES
dc.description.references Takahashi, J, Hashimoto, T, Konno, R, Sugawara, S, Ouchi, K, Oshima, S, Akyu, T, Itoh, Y (2014). An IWAPU STD system for OOV query terms and spoken queries. In Proc. of NTCIR-11. National Institute of Informatics, Tokyo, (pp. 384–389). es_ES
dc.description.references Makino, M, & Kai, A (2014). Combining subword and state-level dissimilarity measures for improved spoken term detection in NTCIR-11 SpokenQuery & Doc task. In Proc. of NTCIR-11. National Institute of Informatics, Tokyo, (pp. 413–418). es_ES
dc.description.references Konno, R, Ouchi, K, Obara, M, Shimizu, Y, Chiba, T, Hirota, T, Itoh, Y (2016). An STD system using multiple STD results and multiple rescoring method for NTCIR-12 SpokenQuery & Doc task. In Proc. of NTCIR-12. National Institute of Informatics, Tokyo, (pp. 200–204). es_ES
dc.description.references Sakamoto, N, Yamamoto, K, Nakagawa, S (2015). Combination of syllable based N-gram search and word search for spoken term detection through spoken queries and IV/OOV classification. In Proc. of ASRU. IEEE, New York, (pp. 200–206). es_ES
dc.description.references Hou, J, Pham, VT, Leung, C-C, Wang, L, 2, HX, Lv, H, Xie, L, Fu, Z, Ni, C, Xiao, X, Chen, H, Zhang, S, Sun, S, Yuan, Y, Li, P, Nwe, TL, Sivadas, S, Ma, B, Chng, ES, Li, H (2015). The NNI Query-by-Example system for MediaEval 2015. In Proc. of MediaEval. Ruzica Piskac, New Haven, (pp. 141–143). es_ES
dc.description.references Vavrek, J, Viszlay, P, Lojka, M, Pleva, M, Juhar, J, Rusko, M (2015). TUKE at MediaEval 2015 QUESST. In Proc. of MediaEval. Ruzica Piskac, New Haven, (pp. 451–453). es_ES
dc.description.references Mantena, G, Achanta, S, Prahallad, K (2014). Query-by-example spoken term detection using frequency domain linear prediction and non-segmental dynamic time warping. IEEE/ACM Transactions on Audio, Speech and Language Processing, 22(5), 946–955. es_ES
dc.description.references Anguera, X, & Ferrarons, M (2013). Memory efficient subsequence DTW for query-by-example spoken term detection. In Proc. of ICME. IEEE, New York, (pp. 1–6). es_ES
dc.description.references Tulsiani, H, & Rao, P (2015). The IIT-B Query-by-Example system for MediaEval 2015. In Proc. of MediaEval. Ruzica Piskac, New Haven, (pp. 341–343). es_ES
dc.description.references Bouallegue, M, Senay, G, Morchid, M, Matrouf, D, Linares, G, Dufour, R (2013). LIA@MediaEval 2013 spoken web search task: An I-Vector based approach. In Proc. of MediaEval. Ruzica Piskac, New Haven, (pp. 771–772). es_ES
dc.description.references Rodriguez-Fuentes, LJ, Varona, A, Penagarikano, M, Bordel, G, Diez, M (2013). GTTS systems for the SWS task at MediaEval 2013. In Proc. of MediaEval. Ruzica Piskac, New Haven, (pp. 831–832). es_ES
dc.description.references Wang, H, Lee, T, Leung, C-C, Ma, B, Li, H (2013). Using parallel tokenizers with DTW matrix combination for low-resource spoken term detection. In Proc. of ICASSP. IEEE, New York, (pp. 8545–8549). es_ES
dc.description.references Wang, H, & Lee, T (2013). The CUHK spoken web search system for MediaEval 2013. In Proc. of MediaEval. Ruzica Piskac, New Haven, (pp. 681–682). es_ES
dc.description.references Proenca, J, Veiga, A, Perdigão, F (2014). The SPL-IT query by example search on speech system for MediaEval 2014. In Proc. of MediaEval. Ruzica Piskac, New Haven, (pp. 741–742). es_ES
dc.description.references Proenca, J, Veiga, A, Perdigao, F (2015). Query by example search with segmented dynamic time warping for non-exact spoken queries. In Proc. of EUSIPCO. Springer, Berlin, (pp. 1691–1695). es_ES
dc.description.references Proenca, J, Castela, L, Perdigao, F (2015). The SPL-IT-UC Query by Example search on speech system for MediaEval 2015. In Proc. of MediaEval. Ruzica Piskac, New Haven, (pp. 471–473). es_ES
dc.description.references Proenca, J, & Perdigao, F (2016). Segmented dynamic time warping for spoken Query-by-Example search. In Proc. of Interspeech. ISCA, Baixas, (pp. 750–754). es_ES
dc.description.references Lopez-Otero, P, Docio-Fernandez, L, Garcia-Mateo, C (2015). GTM-UVigo systems for the Query-by-Example search on speech task at MediaEval 2015. In Proc. of MediaEval. Ruzica Piskac, New Haven, (pp. 521–523). es_ES
dc.description.references Lopez-Otero, P, Docio-Fernandez, L, Garcia-Mateo, C (2015). Phonetic unit selection for cross-lingual Query-by-Example spoken term detection. In Proc. of ASRU. IEEE, New York, (pp. 223–229). es_ES
dc.description.references Saxena, A, & Yegnanarayana, B (2015). Distinctive feature based representation of speech for Query-by-Example spoken term detection. In Proc. of Interspeech. ISCA, Baixas, (pp. 3680–3684). es_ES
dc.description.references Skacel, M, & Szöke, I (2015). BUT QUESST 2015 system description. In Proc. of MediaEval. Ruzica Piskac, New Haven, (pp. 721–723). es_ES
dc.description.references Chen, H, Leung, C-C, Xie, L, Ma, B, Li, H (2016). Unsupervised bottleneck features for low-resource Query-by-Example spoken term detection. In Proc. of Interspeech. ISCA, Baixas, (pp. 923–927). es_ES
dc.description.references Yuan, Y, Leung, C-C, Xie, L, Chen, H, Ma, B, Li, H (2017). Pairwise learning using multi-lingual bottleneck features for low-resource Query-by-Example spoken term detection. In Proc. of ICASSP. IEEE, New York, (pp. 5645–5649). es_ES
dc.description.references Torbati, AHHN, & Picone, J (2016). A nonparametric Bayesian approach for spoken term detection by example query. In Proc. of Interspeech. ISCA, Baixas, (pp. 928–932). es_ES
dc.description.references Popli, A, & Kumar, A (2015). Query-by-example spoken term detection using low dimensional posteriorgrams motivated by articulatory classes. In Proc. of MMSP. IEEE, New York, (pp. 1–6). es_ES
dc.description.references Yang, P, Leung, C-C, Xie, L, Ma, B, Li, H (2014). Intrinsic spectral analysis based on temporal context features for query-by-example spoken term detection. In Proc. of Interspeech. ISCA, Baixas, (pp. 1722–1726). es_ES
dc.description.references George, B, Saxena, A, Mantena, G, Prahallad, K, Yegnanarayana, B (2014). Unsupervised query-by-example spoken term detection using bag of acoustic words and non-segmental dynamic time warping. In Proc. of Interspeech. ISCA, Baixas, (pp. 1742–1746). es_ES
dc.description.references Hazen, TJ, Shen, W, White, CM (2009). Query-by-example spoken term detection using phonetic posteriorgram templates. In Proc. of ASRU. IEEE, New York, (pp. 421–426). es_ES
dc.description.references Abad, A, Astudillo, RF, Trancoso, I (2013). The L2F spoken web search system for mediaeval 2013. In Proc. of MediaEval. Ruzica Piskac, New Haven, (pp. 851–852). es_ES
dc.description.references Szöke, I, Skácel, M, Burget, L (2014). BUT QUESST 2014 system description. In Proc. of MediaEval. Ruzica Piskac, New Haven, (pp. 621–622). es_ES
dc.description.references Szöke, I, Burget, L, Grézl, F, Černocký, JH, Ondel, L (2014). Calibration and fusion of query-by-example systems - BUT SWS 2013. In Proc. of ICASSP. IEEE, New York, (pp. 621–622). es_ES
dc.description.references Abad, A, Rodríguez-Fuentes, LJ, Penagarikano, M, Varona, A, Bordel, G (2013). On the calibration and fusion of heterogeneous spoken term detection systems. In Proc. of Interspeech. ISCA, Baixas, (pp. 20–24). es_ES
dc.description.references Yang, P, Xu, H, Xiao, X, Xie, L, Leung, C-C, Chen, H, Yu, J, Lv, H, Wang, L, Leow, SJ, Ma, B, Chng, ES, Li, H (2014). The NNI query-by-example system for MediaEval 2014. In Proc. of MediaEval. Ruzica Piskac, New Haven, (pp. 691–692). es_ES
dc.description.references Leung, C-C, Wang, L, Xu, H, Hou, J, Pham, VT, Lv, H, Xie, L, Xiao, X, Ni, C, Ma, B, Chng, ES, Li, H (2016). Toward high-performance language-independent Query-by-Example spoken term detection for MediaEval 2015: Post-evaluation analysis. In Proc. of Interspeech. ISCA, Baixas, (pp. 3703–3707). es_ES
dc.description.references Xu, H, Hou, J, Xiao, X, Pham, VT, Leung, C-C, Wang, L, Do, VH, Lv, H, Xie, L, Ma, B, Chng, ES, Li, H (2016). Approximate search of audio queries by using DTW with phone time boundary and data augmentation. In Proc. of ICASSP. IEEE, New York, (pp. 6030–6034). es_ES
dc.description.references Oishi, S, Matsuba, T, Makino, M, Kai, A (2016). Combining state-level and DNN-based acoustic matches for efficient spoken term detection in NTCIR-12 SpokenQuery &Doc-2 task. In Proc. of NTCIR-12. National Institute of Informatics, Tokyo, (pp. 205–210). es_ES
dc.description.references Oishi, S, Matsuba, T, Makino, M, Kai, A (2016). Combining state-level spotting and posterior-based acoustic match for improved query-by-example spoken term detection. In Proc. of Interspeech. ISCA, Baixas, (pp. 740–744). es_ES
dc.description.references Obara, M, Kojima, K, Tanaka, K, Lee, S-w, Itoh, Y (2016). Rescoring by combination of posteriorgram score and subword-matching score for use in Query-by-Example. In Proc. of Interspeech. ISCA, Baixas, (pp. 1918–1922). es_ES
dc.description.references NIST. The Ninth Text REtrieval Conference (TREC 9). http://trec.nist.gov . Accessed Feb 2018. es_ES
dc.description.references Anguera, X, Rodriguez-Fuentes, LJ, Szöke, I, Buzo, A, Metze, F (2014). Query by Example Search on Speech at Mediaeval 2014. In Proc. of MediaEval. Ruzica Piskac, New Haven, (pp. 351–352). es_ES
dc.description.references Joho, H, & Kishida, K (2014). Overview of the NTCIR-11 SpokenQuery&Doc Task. In Proc. of NTCIR-11. National Institute of Informatics, Tokyo, (pp. 1–7). es_ES
dc.description.references NIST. Draft KWS16 Keyword Search Evaluation Plan. https://www.nist.gov/sites/default/files/documents/itl/iad/mig/KWS16-evalplan-v04.pdf . Accessed Feb 2018. es_ES
dc.description.references Anguera, X, Metze, F, Buzo, A, Szöke, I, Rodriguez-Fuentes, LJ (2013). The spoken web search task. In Proc. of MediaEval. Ruzica Piskac, New Haven, (pp. 921–922). es_ES
dc.description.references Taras, B, & Nadeu, C (2011). Audio segmentation of broadcast news in the Albayzin-2010 evaluation: overview, results, and discussion. EURASIP Journal on Audio, Speech, and Music Processing, 2011(1), 1–10. es_ES
dc.description.references Zelenák, M, Schulz, H, Hernando, J (2012). Speaker diarization of broadcast news in Albayzin 2010 evaluation campaign. EURASIP Journal on Audio, Speech, and Music Processing, 2012(19), 1–9. es_ES
dc.description.references Rodríguez-Fuentes, LJ, Penagarikano, M, Varona, A, Díez, M, Bordel, G (2011). The Albayzin 2010 Language Recognition Evaluation. In Proc. of Interspeech. ISCA, Baixas, (pp. 1529–1532). es_ES
dc.description.references Tejedor, J, Toledano, DT, Lopez-Otero, P, Docio-Fernandez, L, Garcia-Mateo, C, Cardenal, A, Echeverry-Correa, JD, Coucheiro-Limeres, A, Olcoz, J, Miguel, A (2015). Spoken term detection ALBAYZIN 2014 evaluation: overview, systems, results, and discussion. EURASIP, Journal on Audio, Speech and Music Processing, 2015(21), 1–27. es_ES
dc.description.references Tejedor, J, Toledano, DT, Anguera, X, Varona, A, Hurtado, LF, Miguel, A, Colás, J (2013). Query-by-example spoken term detection ALBAYZIN 2012 evaluation: overview, systems, results, and discussion. EURASIP, Journal on Audio, Speech, and Music Processing, 2013(23), 1–17. es_ES
dc.description.references Tejedor, J, Toledano, DT, Lopez-Otero, P, Docio-Fernandez, L, Garcia-Mateo, C (2016). Comparison of ALBAYZIN query-by-example spoken term detection 2012 and 2014 evaluations. EURASIP, Journal on Audio, Speech and Music Processing, 2016(1), 1–19. es_ES
dc.description.references Méndez, F, Docío, L, Arza, M, Campillo, F (2010). The Albayzin 2010 text-to-speech evaluation. In Proc. of FALA. UniversidadeVigo, Vigo, (pp. 317–340). es_ES
dc.description.references Billa, J, Ma, KW, McDonough, JW, Zavaliagkos, G, Miller, DR, Ross, KN, El-Jaroudi, A (1997). Multilingual speech recognition: the 1996 Byblos Callhome system. In Proc. of Eurospeech. ISCA, Baixas, (pp. 363–366). es_ES
dc.description.references Killer, M, Stuker, S, Schultz, T (2003). Grapheme based speech recognition. In Proc. of Eurospeech. ISCA, Baixas, (pp. 3141–3144). es_ES
dc.description.references Burget, L, Schwarz, P, Agarwal, M, Akyazi, P, Feng, K, Ghoshal, A, Glembek, O, Goel, N, Karafiat, M, Povey, D, Rastrow, A, Rose, RC, Thomas, S (2010). Multilingual acoustic modeling for speech recognition based on subspace gaussian mixture models. In Proc. of ICASSP. IEEE, New York, (pp. 4334–4337). es_ES
dc.description.references Cuayahuitl, H, & Serridge, B (2002). Out-of-vocabulary word modeling and rejection for Spanish keyword spotting systems. In Proc. of MICAI. Springer, Berlin, (pp. 156–165). es_ES
dc.description.references Tejedor, J (2009). Contributions to keyword spotting and spoken term detection for information retrieval in audio mining. PhD thesis, Universidad Autónoma de Madrid, Madrid, Spain. es_ES
dc.description.references Tejedor, J, Toledano, DT, Wang, D, King, S, Colás, J (2014). Feature analysis for discriminative confidence estimation in spoken term detection. Computer Speech and Language, 28(5), 1083–1114. es_ES
dc.description.references Li, J, Wang, X, Xu, B (2014). An empirical study of multilingual and low-resource spoken term detection using deep neural networks. In Proc. of Interspeech. ISCA, Baixas, (pp. 1747–1751). es_ES
dc.description.references NIST. The Spoken Term Detection (STD) 2006 evaluation plan. http://berlin.csie.ntnu.edu.tw/Courses/Special%20Topics%20in%20Spoken%20Language%20Processing/Lectures2008/SLP2008S-Lecture12-Spoken%20Term%20Detection.pdf . Accessed Feb 2018. es_ES
dc.description.references Fiscus, JG, Ajot, J, Garofolo, JS, Doddingtion, G (2007). Results of the 2006 spoken term detection evaluation. In Proc. of SSCS. ACM, New York, (pp. 45–50). es_ES
dc.description.references Martin, A, Doddington, G, Kamm, T, Ordowski, M, Przybocki, M (1997). The DET curve in assessment of detection task performance. In Proc. of Eurospeech. ISCA, Baixas, (pp. 1895–1898). es_ES
dc.description.references NIST. Evaluation Toolkit (STDEval) software. https://www.nist.gov/itl/iad/mig/tools . Accessed Feb 2018. es_ES
dc.description.references Union, IT. ITU-T Recommendation P.563: Single-ended method for objective speech quality assessment in narrow-band telephony applications. http://www.itu.int/rec/T-REC-P.563/en . Accessed Feb 2018. es_ES
dc.description.references Rajput, N, & Metze, F (2011). Spoken web search. In Proc. of MediaEval. Ruzica Piskac, New Haven, (pp. 1–2). es_ES
dc.description.references Metze, F, Barnard, E, Davel, M, van Heerden, C, Anguera, X, Gravier, G, Rajput, N (2012). The spoken web search task. In Proc. of MediaEval. Ruzica Piskac, New Haven, (pp. 41–42). es_ES
dc.description.references Szöke, I, Rodriguez-Fuentes, LJ, Buzo, A, Anguera, X, Metze, F, Proenca, J, Lojka, M, Xiong, X (2015). Query by Example Search on Speech at Mediaeval 2015. In Proc. of MediaEval. Ruzica Piskac, New Haven, (pp. 81–82). es_ES
dc.description.references Szöke, I, & Anguera, X (2016). Zero-cost speech recognition task at Mediaeval 2016. In Proc. of MediaEval. Ruzica Piskac, New Haven, (pp. 81–82). es_ES
dc.description.references Akiba, T, Nishizaki, H, Nanjo, H, Jones, GJF (2014). Overview of the NTCIR-11 spokenquery &doc task. In Proc. of NTCIR-11. National Institute of Informatics, Tokyo, (pp. 1–15). es_ES
dc.description.references Akiba, T, Nishizaki, H, Nanjo, H, Jones, GJF (2016). Overview of the NTCIR-12 spokenquery &doc-2. In Proc. of NTCIR-12. National Institute of Informatics, Tokyo, (pp. 1–13). es_ES
dc.description.references Schwarz, P (2008). Phoneme recognition based on long temporal context. PhD thesis, FIT, BUT, Brno, Czech Republic. es_ES
dc.description.references Varona, A, Penagarikano, M, Rodríguez-Fuentes, LJ, Bordel, G (2011). On the use of lattices of time-synchronous cross-decoder phone co-occurrences in a SVM-phonotactic language recognition system. In Proc. of Interspeech. ISCA, Baixas, (pp. 2901–2904). es_ES
dc.description.references Eyben, F, Wollmer, M, Schuller, B (2010). OpenSMILE—the munich versatile and fast open-source audio feature extractor. In Proc. of ACM Multimedia (MM). ACM, New York, (pp. 1459–1462). es_ES
dc.description.references Lopez-Otero, P, Docio-Fernandez, L, Garcia-Mateo, C (2016). Finding relevant features for zero-resource query-by-example search on speech. Speech Communication, 84(1), 24–35. es_ES
dc.description.references Zhang, Y, & Glass, JR (2009). Unsupervised spoken keyword spotting via segmental DTW on Gaussian posteriorgrams. In Proc. of ASRU. IEEE, New York, (pp. 398–403). es_ES
dc.description.references Povey, D, Ghoshal, A, Boulianne, G, Burget, L, Glembek, O, Goel, N, Hannemann, M, Motlicek, P, Qian, Y, Schwarz, P, Silovsky, J, Stemmer, G, Vesely, K (2011). The KALDI speech recognition toolkit. In Proc. of ASRU. IEEE, New York, (pp. 1–4). es_ES
dc.description.references Muller, M. (2007). Information retrieval for music and motion. New York: Springer. es_ES
dc.description.references Szöke, I, Skacel, M, Burget, L (2014). BUT QUESST 2014 system description. In Proc. of MediaEval. Ruzica Piskac, New Haven, (pp. 621–622). es_ES
dc.description.references Brümmer, N, & van Leeuwen, D (2006). On calibration of language recognition scores. In Proc of the IEEE Odyssey: The speaker and language recognition workshop. IEEE, New York, (pp. 1–8). es_ES
dc.description.references Brümmer, N, & de Villiers, E. The BOSARIS toolkit user guide: Theory, algorithms and code for binary classifier score processing. Technical report. https://sites.google.com/site/nikobrummer . Accessed Feb 2018. es_ES
dc.description.references Meinedo, H, & Neto, J (2005). A stream-based audio segmentation, classification and clustering pre-processing system for broadcast news using ANN models. In Proc. of Interspeech. ISCA, Baixas, (pp. 237–240). es_ES
dc.description.references Morgan, N, & Bourlard, H (1995). An introduction to hybrid HMM/connectionist continuous speech recognition. IEEE Signal Processing Magazine, 12(3), 25–42. es_ES
dc.description.references Meinedo, H, Abad, A, Pellegrini, T, Trancoso, I, Neto, J (2010). The L2F broadcast news speech recognition system. In Proc. of FALA. UniversidadeVigo, Vigo, (pp. 93–96). es_ES
dc.description.references Abad, A, Luque, J, Trancoso, I (2011). Parallel transformation network features for speaker recognition. In Proc. of ICASSP. IEEE, New York, (pp. 5300–5303). es_ES
dc.description.references Diez, M, Varona, A, Penagarikano, M, Rodriguez-Fuentes, LJ, Bordel, G (2012). On the use of phone log-likelihood ratios as features in spoken language recognition. In Proc. of SLT. IEEE, New York, (pp. 274–279). es_ES
dc.description.references Diez, M, Varona, A, Penagarikano, M, Rodriguez-Fuentes, LJ, Bordel, G (2014). New insight into the use of phone log-likelihood ratios as features for language recognition. In Proc. of Interspeech. ISCA, Baixas, (pp. 1841–1845). es_ES
dc.description.references Abad, A, Ribeiro, E, Kepler, F, Astudillo, R, Trancoso, I (2016). Exploiting phone log-likelihood ratio features for the detection of the native language of non-native English speakers. In Proc. of Interspeech. ISCA, Baixas, (pp. 2413–2417). es_ES
dc.description.references Rodríguez-Fuentes, LJ, Varona, A, Peñagarikano, M, Bordel, G, Díez, M (2014). High-performance query-by-example spoken term detection on the SWS 2013 evaluation. In Proc. of ICASSP. IEEE, New York, (pp. 7819–7823). es_ES
dc.description.references Vesely, K, Ghoshal, A, Burget, L, Povey, D (2013). Sequence-discriminative training of deep neural networks. In Proc. of Interspeech. ISCA, Baixas, (pp. 2345–2349). es_ES
dc.description.references Ghahremani, P, BabaAli, B, Povey, D, Riedhammer, K, Trmal, J, Khudanpur, S (2014). A pitch extraction algorithm tuned for automatic speech recognition. In Proc. of ICASSP. IEEE, New York, (pp. 2494–2498). es_ES
dc.description.references Povey, D, Hannemann, M, Boulianne, G, Burget, L, Ghoshal, A, Janda, M, Karafiat, M, Kombrink, S, Motlicek, P, Qian, Y, Riedhammer, K, Vesely, K, Vu, NT (2012). Generating exact lattices in the WFST framework. In Proc. of ICASSP. IEEE, New York, (pp. 4213–4216). es_ES
dc.description.references Garcia-Mateo, C, Dieguez-Tirado, J, Docio-Fernandez, L, Cardenal-Lopez, A (2004). Transcrigal: A bilingual system for automatic indexing of broadcast news. In Proc. of LREC. ELRA, Paris, (pp. 2061–2064). es_ES
dc.description.references Stolcke, A (2002). SRILM—an extensible language modeling toolkit. In Proc. of Interspeech. ISCA, Baixas, (pp. 901–904). es_ES
dc.description.references Lopez-Otero, P, Docio-Fernandez, L, Garcia-Mateo, C (2016). GTM-UVigo systems for Albayzin 2016 search on speech evaluation. In Proc. of Iberspeech. Springer, Berlin, (pp. 65–74). es_ES
dc.description.references Chen, G, Khudanpur, S, Povey, D, Trmal, J, Yarowsky, D, Yilmaz, O (2013). Quantifying the value of pronunciation lexicons for keyword search in low resource languages. In Proc. of ICASSP. IEEE, New York, (pp. 8560–8564). es_ES
dc.description.references Pham, VT, Chen, NF, Sivadas, S, Xu, H, Chen, I-F, Ni, C, Chng, ES, Li, H (2014). System and keyword dependent fusion for spoken term detection. In Proc. of SLT. IEEE, New York, (pp. 430–435). es_ES
dc.description.references Can, D, & Saraclar, M (2011). Lattice indexing for spoken term detection. IEEE Transactions on Audio, Speech and Language Processing, 19(8), 2338–2347. es_ES
dc.description.references Miller, DRH, Kleber, M, Kao, C-L, Kimball, O, Colthurst, T, Lowe, SA, Schwartz, RM, Gish, H (2007). Rapid and accurate spoken term detection. In Proc. of Interspeech. ISCA, Baixas, (pp. 314–317). es_ES


Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem