Note on Translation Introduction by Michael Holquist Response to a Question from the Novy Mir Editorial Staff The Bildungsroman and Its Significance in the History of Realism (Toward a Historical Typology of the Novel) The Problem of Speech Genres The Problem of the Text in Linguistics, Philology, and the Human Sciences: An Experiment in Philosophical Analysis From Notes Made in 1970-71 Toward a Methodology for the Human Sciences Index

Speech Genres and Other Late Essays

Digital processing of speech signals

http://mi.eng.cam.ac.uk/~sjy/papers/wiyo07.pdf

Partially observable Markov decision processes for spoken dialog systems

http://www.eis.mdx.ac.uk/staffpages/juanaugusto/CookAJ2009.pdf

Review: Ambient intelligence: Technologies, applications, and opportunities

We have collected a corpus of data from natural meetings that occurred at the International Computer Science Institute (ICSI) in Berkeley, California over the last three years The corpus contains audio recorded simultaneously from head-worn and table-top microphones, word-level transcripts of meetings, and various metadata on participants, meetings, and hardware Such a corpus supports work in automatic speech recognition, noise robustness, dialog modeling, prosody, rich transcription, information retrieval, and more We present details on the contents of the corpus, as well as rationales for the decisions that led to its configuration The corpus were delivered to the Linguistic Data Consortium (LDC)

/pdf/the-icsi-meeting-corpus-1hle0448sk.pdf

The ICSI Meeting Corpus

For many practical applications of speech recognition systems, it is desirable to have an estimate of confidence for each hypothesized word, i.e. to have an estimate of which words of the output of the speech recognizer are likely to be correct and which are not reliable. We describe the development of the measure of the confidence tagger JANKA, which is able to provide confidence information for the words at the output of the speech recognizer JANUS-3-SR. On a spontaneous German human-to-human database, JANKA achieves a tagging accuracy of 90% at a baseline word accuracy of 82%.

/pdf/confidence-measures-for-spontaneous-speech-recognition-3sjd2hy6p2.pdf

Confidence measures for spontaneous speech recognition

This paper describes the Ephyra question answering engine, a modular and extensible framework that allows to integrate multiple approaches to question answering in one system Our framework can be adapted to languages other than English by replacing language-specific components It supports the two major approaches to question answering, knowledge annotation and knowledge mining Ephyra uses the web as a data resource, but could also work with smaller corpora In addition, we propose a novel approach to question interpretation which abstracts from the original formulation of the question Text patterns are used to interpret a question and to extract answers from text snippets Our system automatically learns the patterns for answer extraction, using question-answer pairs as training data Experimental results revealed the potential of this approach.

/pdf/a-pattern-learning-approach-to-question-answering-within-the-4rpvnlhbtb.pdf

A pattern learning approach to question answering within the ephyra framework

Speaker adaptation with all-pass transforms

The speech-to-speech translation system Verbmobil requires a multilingual setting. This consists of recognition engines in the three languages German, English and Japanese that run in one common framework together with a language identification component which is able to switch between these recognizers. This article describes the challenges of multilingual speech recognition and presents different solutions to the problem of the automatic language identification task. The combination of the described components results in a flexible and user-friendly multilingual spoken dialog system.

/pdf/multilingual-speech-recognition-5c08ebx8qv.pdf

Multilingual Speech Recognition

Archiving, indexing, and later browsing through stored presentations and lectures is a task that can be observed with a growing frequency. We have investigated the special problems and advantages of lectures and propose the design and adaptation of a speech recognizer towards a lecture such that the recognition accurucy can be significantly improved by prior analysis of the presented documents using a special class-based language model. We defined a tracking accuracy measure which measures how well a system can automatically align recognized words with parts of a presentation and show that by prior exploitation of the presented documents, the trucking accuracy can be improved. The system described in this paper is part of an intelligent meeting room developed in the European- Union-sponsored project FAME (Facilitating Agent for Multicultural Exchange).

Lecture and presentation tracking in an intelligent meeting room

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