This paper describes the GTH-UPM system for the Albayzin 2014 Search on Speech Evaluation. Teh evaluation task consists of searching a list of terms/queries in audio files. The GTH-UPM system we are presenting is based on a LVCSR (Large Vocabulary Continuous Speech Recognition) system. We have used MAVIR corpus and the Spanish partition of the EPPS (European Parliament Plenary Sessions) database for training both acoustic and language models. The main effort has been focused on lexicon preparation and text selection for the language model construction. The system makes use of different lexicon and language models depending on the task that is performed. For the best configuration of the system on the development set, we have obtained a FOM of 75.27 for the deyword spotting task.
Within search-on-speech, Spoken Term Detection (STD) aims to retrieve data from a speech repository given a textual representation of a search term. This paper presents an international open evaluation for search-on-speech based on STD in Spanish and an analysis of the results. The evaluation has been designed carefully so that several analyses of the main results can be carried out. The evaluation consists in retrieving the speech files that contain the search terms, providing their start and end times, and a score value that reflects the confidence given to the detection. Two different Spanish speech databases have been employed in the evaluation: MAVIR database, which comprises a set of talks from workshops, and EPIC database, which comprises a set of European Parliament sessions in Spanish. We present the evaluation itself, both databases, the evaluation metric, the systems submitted to the evaluation, the results, and a detailed discussion. Five different research groups took part in the evaluation, and ten different systems were submitted in total. We compare the systems submitted to the evaluation and make a deep analysis based on some search term properties (term length, within-vocabulary/out-of-vocabulary terms, single-word/multi-word terms, and native (Spanish)/foreign terms).
Within search-on-speech, Spoken Term Detection (STD) aims to retrieve data from a speech repository given a textual representation of a search term. This paper presents an international open evaluation for search-on-speech based on STD in Spanish and an analysis of the results. The evaluation has been designed carefully so that several analyses of the main results can be carried out. The evaluation consists in retrieving the speech files that contain the search terms, providing their start and end times, and a score value that reflects the confidence given to the detection. Two different Spanish speech databases have been employed in the evaluation: MAVIR database, which comprises a set of talks from workshops, and EPIC database, which comprises a set of European Parliament sessions in Spanish. We present the evaluation itself, both databases, the evaluation metric, the systems submitted to the evaluation, the results, and a detailed discussion. Five different research groups took part in the evaluation, and ten different systems were submitted in total. We compare the systems submitted to the evaluation and make a deep analysis based on some search term properties (term length, within-vocabulary/out-of-vocabulary terms, single-word/multi-word terms, and native (Spanish)/foreign terms) ; Xunta de Galicia | Ref. ED431G/01 ; Ministerio de Economía y Competitividad | Ref. TEC2015-67163-C2-1-R ; Ministerio de Economía y Competitividad | Ref. TIN2014-54288-C4-1-R ; Ministerio de Economía y Competitividad | Ref. TEC2015-68172-C2-1-P
Within search-on-speech, Spoken Term Detection (STD) aims to retrieve data from a speech repository given a textual representation of a search term. This paper presents an international open evaluation for search-on-speech based on STD in Spanish and an analysis of the results. The evaluation has been designed carefully so that several analyses of the main results can be carried out. The evaluation consists in retrieving the speech files that contain the search terms, providing their start and end times, and a score value that reflects the confidence given to the detection. Two different Spanish speech databases have been employed in the evaluation: MAVIR database, which comprises a set of talks from workshops, and EPIC database, which comprises a set of European Parliament sessions in Spanish. We present the evaluation itself, both databases, the evaluation metric, the systems submitted to the evaluation, the results, and a detailed discussion. Five different research groups took part in the evaluation, and ten different systems were submitted in total. We compare the systems submitted to the evaluation and make a deep analysis based on some search term properties (term length, within-vocabulary/out-of-vocabulary terms, single-word/multi-word terms, and native (Spanish)/foreign terms) ; Xunta de Galicia | Ref. ED431G/01 ; Ministerio de Economía y Competitividad | Ref. TEC2015-67163-C2-1-R ; Ministerio de Economía y Competitividad | Ref. TIN2014-54288-C4-1-R ; Ministerio de Economía y Competitividad | Ref. TEC2015-68172-C2-1-P
The electronic version of this article is the complete one and can be found online at: http://dx.doi.org/10.1186/s13636-015-0063-8 ; Spoken term detection (STD) aims at retrieving data from a speech repository given a textual representation of the search term. Nowadays, it is receiving much interest due to the large volume of multimedia information. STD differs from automatic speech recognition (ASR) in that ASR is interested in all the terms/words that appear in the speech data, whereas STD focuses on a selected list of search terms that must be detected within the speech data. This paper presents the systems submitted to the STD ALBAYZIN 2014 evaluation, held as a part of the ALBAYZIN 2014 evaluation campaign within the context of the IberSPEECH 2014 conference. This is the first STD evaluation that deals with Spanish language. The evaluation consists of retrieving the speech files that contain the search terms, indicating their start and end times within the appropriate speech file, along with a score value that reflects the confidence given to the detection of the search term. The evaluation is conducted on a Spanish spontaneous speech database, which comprises a set of talks from workshops and amounts to about 7 h of speech. We present the database, the evaluation metrics, the systems submitted to the evaluation, the results, and a detailed discussion. Four different research groups took part in the evaluation. Evaluation results show reasonable performance for moderate out-of-vocabulary term rate. This paper compares the systems submitted to the evaluation and makes a deep analysis based on some search term properties (term length, in-vocabulary/out-of-vocabulary terms, single-word/multi-word terms, and in-language/foreign terms). ; This work has been partly supported by project CMC-V2 (TEC2012-37585-C02-01) from the Spanish Ministry of Economy and Competitiveness. This research was also funded by the European Regional Development Fund, the Galician Regional Government (GRC2014/024, "Consolidation of Research Units: AtlantTIC Project" CN2012/160).
