Xem 1-7 trên 7 kết quả Asr applications
  • Chapters in the first part of the book cover all the essential speech processing techniques for building robust, automatic speech recognition systems: the representation for speech signals and the methods for speech-features extraction, acoustic and language modeling, efficient algorithms for searching the hypothesis space, and multimodal approaches to speech recognition.

    pdf576p kimngan_1 06-11-2012 22 5   Download

  • We will demonstrate a novel graphical interface for correcting search errors in the output of a speech recognizer. This interface allows the user to visualize the word lattice by “pulling apart” regions of the hypothesis to reveal a cloud of words simlar to the “tag clouds” popular in many Web applications. This interface is potentially useful for dictation on portable touchscreen devices such as the Nokia N800 and other mobile Internet devices.

    pdf3p hongphan_1 15-04-2013 18 2   Download

  • In the EMIME project we have studied unsupervised cross-lingual speaker adaptation. We have employed an HMM statistical framework for both speech recognition and synthesis which provides transformation mechanisms to adapt the synthesized voice in TTS (text-to-speech) using the recognized voice in ASR (automatic speech recognition). An important application for this research is personalised speech-to-speech translation that will use the voice of the speaker in the input language to utter the translated sentences in the output language. ...

    pdf6p hongdo_1 12-04-2013 11 3   Download

  • Mobile voice-enabled search is emerging as one of the most popular applications abetted by the exponential growth in the number of mobile devices. The automatic speech recognition (ASR) output of the voice query is parsed into several fields. Search is then performed on a text corpus or a database. In order to improve the robustness of the query parser to noise in the ASR output, in this paper, we investigate two different methods to query parsing.

    pdf8p bunthai_1 06-05-2013 10 2   Download

  • We use an EM algorithm to learn user models in a spoken dialog system. Our method requires automatically transcribed (with ASR) dialog corpora, plus a model of transcription errors, but does not otherwise need any manual transcription effort. We tested our method on a voice-controlled telephone directory application, and show that our learned models better replicate the true distribution of user actions than those trained by simpler methods and are very similar to user models estimated from manually transcribed dialogs. ...

    pdf4p hongphan_1 15-04-2013 14 1   Download

  • This paper proposes a named entity recognition (NER) method for speech recognition results that uses confidence on automatic speech recognition (ASR) as a feature. The ASR confidence feature indicates whether each word has been correctly recognized. The NER model is trained using ASR results with named entity (NE) labels as well as the corresponding transcriptions with NE labels.

    pdf8p hongvang_1 16-04-2013 27 1   Download

  • This paper presents the application of WordNet-based semantic relatedness measures to Automatic Speech Recognition (ASR) in multi-party meetings. Different word-utterance context relatedness measures and utterance-coherence measures are defined and applied to the rescoring of N best lists. No significant improvements in terms of Word-Error-Rate (WER) are achieved compared to a large word-based ngram baseline model. We discuss our results and the relation to other work that achieved an improvement with such models for simpler tasks. ...

    pdf4p hongvang_1 16-04-2013 16 1   Download

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