| 1. |
- Neiberg, Daniel, et al.
(författare)
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Emotion Recognition in Spontaneous Speech Using GMMs
- 2006
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Ingår i: INTERSPEECH 2006 AND 9TH INTERNATIONAL CONFERENCE ON SPOKEN LANGUAGE PROCESSING. - BAIXAS : ISCA-INST SPEECH COMMUNICATION ASSOC. ; , s. 809-812, s. 101-104
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Konferensbidrag (refereegranskat)abstract
- Automatic detection of emotions has been evaluated using standard Mel-frequency Cepstral Coefficients, MFCCs, and a variant, MFCC-low, calculated between 20 and 300 Hz, in order to model pitch. Also plain pitch features have been used. These acoustic features have all been modeled by Gaussian mixture models, GMMs, on the frame level. The method has been tested on two different corpora and languages; Swedish voice controlled telephone services and English meetings. The results indicate that using GMMs on the frame level is a feasible technique for emotion classification. The two MFCC methods have similar performance, and MFCC-low outperforms the pitch features. Combining the three classifiers significantly improves performance.
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| 2. |
- Larsson, Staffan, 1969, et al.
(författare)
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Corrective feedback and concept updates
- 2008
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Ingår i: Carlson et al (eds.): Proceedings of The second Swedish Language Technology Conference (SLTC-08).
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Tidskriftsartikel (refereegranskat)
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| 3. |
- Kokkinakis, Dimitrios, 1965
(författare)
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Shallow Features for Differentiating Disease-Treatment Relations using Supervised Learning, a pilot study
- 2009
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Ingår i: Proceedings of the 12th International Conference TSD (Text, Speech and Dialogue). Springer Verlag, LNCS/LNAI series.. ; 5729, s. 395-402
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Clinical narratives provide an information rich, nearly unexplored corpus of evidential knowledge that is considered as a challenge for practitioners in the language technology field, particularly because of the nature of the texts (excessive use of terminology, abbreviations, orthographic term variation), the significant opportunities for clinical research that such material can provide and the potentially broad impact that clinical findings may have in every day life. It is therefore recognized that the capability to automatically extract key concepts and their relationships from such data will allow systems to properly understand the content and knowledge embedded in the free text which can be of great value for applications such as information extraction and question & answering. This paper gives a brief presentation of such textual data and its semantic annotation, and discuss the set of semantic relations that can be observed between diseases and treatments in the sample. The problem is then designed as a machine learning task in which the relations are tried to be learned in a supervised fashion, using pre-annotated data. The challenges designing the problem and empirical results are presented.
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| 4. |
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| 5. |
- Olsson, Fredrik, 1971
(författare)
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Bootstrapping Named Entity Annotation by Means of Active Machine Learning
- 2008
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- This thesis describes the development and in-depth empirical investigation of a method, called BootMark, for bootstrapping the marking up of named entities in textual documents. The reason for working with documents, as opposed to for instance sentences or phrases, is that the BootMark method is concerned with the creation of corpora. The claim made in the thesis is that BootMark requires a human annotator to manually annotate fewer documents in order to produce a named entity recognizer with a given performance, than would be needed if the documents forming the basis for the recognizer were randomly drawn from the same corpus. The intention is then to use the created named entity recognizer as a pre-tagger and thus eventually turn the manual annotation process into one in which the annotator reviews system-suggested annotations rather than creating new ones from scratch. The BootMark method consists of three phases: (1) Manual annotation of a set of documents; (2) Bootstrapping -- active machine learning for the purpose of selecting which document to annotate next; (3) The remaining unannotated documents of the original corpus are marked up using pre-tagging with revision. Five emerging issues are identified, described and empirically investigated in the thesis. Their common denominator is that they all depend on the realization of the named entity recognition task, and as such, require the context of a practical setting in order to be properly addressed. The emerging issues are related to: (1) the characteristics of the named entity recognition task and the base learners used in conjunction with it; (2) the constitution of the set of documents annotated by the human annotator in phase one in order to start the bootstrapping process; (3) the active selection of the documents to annotate in phase two; (4) the monitoring and termination of the active learning carried out in phase two, including a new intrinsic stopping criterion for committee-based active learning; and (5) the applicability of the named entity recognizer created during phase two as a pre-tagger in phase three. The outcomes of the empirical investigations concerning the emerging issues support the claim made in the thesis. The results also suggest that while the recognizer produced in phases one and two is as useful for pre-tagging as a recognizer created from randomly selected documents, the applicability of the recognizer as a pre-tagger is best investigated by conducting a user study involving real annotators working on a real named entity recognition task.
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| 6. |
- Argaw, Atelach Alemu, et al.
(författare)
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Dictionary-based Amharic-French information retrieval
- 2006
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Ingår i: Accessing Multilingual Information Repositories. - Berlin, Heidelberg : Springer Berlin Heidelberg. - 354045697X ; , s. 83-92, s. 83-92
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Konferensbidrag (refereegranskat)abstract
- We present four approaches to the Amharic - French bilingual track at CLEF 2005. All experiments use a dictionary based approach to translate the Amharic queries into French Bags-of-words, but while one approach uses word sense discrimination on the translated side of the queries, the other one includes all senses of a translated word in the query for searching. We used two search engines: The SICS experimental engine and Lucene, hence four runs with the two approaches. Non-content bearing words were removed both before and after the dictionary lookup. TF/IDF values supplemented by a heuristic function was used to remove the stop words from the Amharic queries and two French stopwords lists were used to remove them from the French translations. In our experiments, we found that the SICS search engine performs better than Lucene and that using the word sense discriminated keywords produce a slightly better result than the full set of non discriminated keywords.
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| 7. |
- Boye, Johan, et al.
(författare)
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Robust parsing and spoken negotiative dialogue with databases
- 2008
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Ingår i: Natural Language Engineering. - : Cambridge University Press. - 1351-3249 .- 1469-8110. ; 14:3, s. 289-312
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Tidskriftsartikel (refereegranskat)abstract
- This paper presents a robust parsing algorithm and semantic formalism for the interpretation of utterances in spoken negotiative dialogue with databases. The algorithm works in two passes: a domain-specific pattern-matching phase and a domain-independent semantic analysis phase. Robustness is achieved by limiting the set of representable utterance types to an empirically motivated subclass which is more expressive than propositional slot–value lists, but much less expressive than first-order logic. Our evaluation shows that in actual practice the vast majority of utterances that occur can be handled, and that the parsing algorithm is highly efficient and accurate.
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| 8. |
- Gey, Frederic, et al.
(författare)
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Information access in a multilingual world: transitioning from research to real-world applications
- 2009. - 5
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Ingår i: SIGIR Forum. - Kista, Sweden : Swedish Institute of Computer Science. - 0163-5840 .- 1558-0229. ; 43, s. 24-28
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- This report constitutes the proceedings of the workshop on Information Access in a Multilingual World: Transitioning from Research to Real-World Applications}, held at SIGIR 2009 in Boston, July 23, 2009. Multilingual Information Access (MLIA) is at a turning point wherein substantial real-world applications are being introduced after fifteen years of research into cross-language information retrieval, question answering, statistical machine translation and named entity recognition. Previous workshops on this topic have focused on research and small-scale applications. The focus of this workshop was on technology transfer from research to applications and on what future research needs to be done which facilitates MLIA in an increasingly connected multilingual world.
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| 9. |
- Rosell, Magnus, et al.
(författare)
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Global Evaluation of Random Indexing through Swedish Word Clustering Compared to the People’s Dictionary of Synonyms
- 2009
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Ingår i: Proceedings of the International Conference RANLP-2009. ; , s. 376-380
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Konferensbidrag (refereegranskat)abstract
- Evaluation of word space models is usually local in the sense that it only considers words that are deemed very similar by the model. We propose a global evaluation scheme based on clustering of the words. A clustering of high quality in an external evaluation against a semantic resource, such as a dictionary of synonyms, indicates a word space model of high quality. We use Random Indexing to create several different models and compare them by clustering evaluation against the People's Dictionary of Synonyms, a list of Swedish synonyms that are graded by the public. Most notably we get better results for models based on syntagmatic information (words that appear together) than for models based on paradigmatic information (words that appear in similar contexts). This is quite contrary to previous results that have been presented for local evaluation. Clusterings to ten clusters result in a recall of 83% for a syntagmatic model, compared to 34% for a comparable paradigmatic model, and 10% for a random partition.
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| 10. |
- Sahlgren, Magnus, et al.
(författare)
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Automatic Bilingual Lexicon Acquisition Using Random Indexing of Parallel Corpora
- 2005
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Ingår i: Natural Language Engineering. - 1351-3249 .- 1469-8110. ; 11:3, s. 327-341
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Tidskriftsartikel (refereegranskat)abstract
- This paper presents a very simple and effective approach to using parallel corpora for automatic bilingual lexicon acquisition. The approach, which uses the Random Indexing vector space methodology, is based on finding correlations between terms based on their distributional characteristics. The approach requires a minimum of preprocessing and linguistic knowledge, and is efficient, fast and scalable. In this paper, we explain how our approach differs from traditional cooccurrence-based word alignment algorithms, and we demonstrate how to extract bilingual lexica using the Random Indexing approach applied to aligned parallel data. The acquired lexica are evaluated by comparing them to manually compiled gold standards, and we report overlap of around 60%. We also discuss methodological problems with evaluating lexical resources of this kind.
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