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Titlebook: Computational Processing of the Portuguese Language; 8th International Co António Teixeira,Vera Lúcia Strube Lima,Paulo Quar Conference pro

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Frication and Voicing Classificatione voicing and f0 values. Log - energy and Mel frequency cepstral features were used to train a Gaussian classifier that objectively labeled speech frames for frication. Duration statistics were derived from the voicing and frication labels for distinguishing between unvoiced and voiced fricatives in British English and European Portuguese.
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Comparing Window and Syntax Based Strategies for Semantic Extractionased on syntactic contexts with two strategies relying on windows of tagged words, one using word order and the other bags of words. On a Portuguese corpus of 12 million words, syntactic contexts produce significantly better results for both frequent and not very frequent words.
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Learning Coreference Resolution for Portuguese Texts any type of noun phrases for Portuguese. The system was trained and tested in a journalistic corpus formed by 50 texts with a total of 5047 markables. Both the induced classifier and the anaphoric clustering algorithm were evaluated using appropriate metrics. The clustering evalution was performed using the MUC and .. scorers.
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A Platform of Distributed Speech Recognition for the European Portuguese Languagems such as PDAs. The obtained system has no significant degradation in what concerns word error rates or increased latency in processing, and only a small increase in word error rate when the audio is recorded using the microphone in the device.
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