Automatic transcription of conversational telephone speech

Hain, Thomas; Woodland, Philip C.; Evermann, G.; Gales, Mjf; Liu, Xunying; Moore, G.L.; Povey, Daniel; Wang, Lan

doi:10.1109/tsa.2005.852999

Cited by 20 publications

(11 citation statements)

References 28 publications

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“…In the speech community, there are two main associations that sell valuable speech databases for research and development: they are LDC (Linguistic Data Consortium: http://www.ldc.upenn.edu/) and ELRA (European Language Resources Association: http://www.elra.info/). In [11], there is a very good review of the state of art focusing on acoustic modeling for speech recognition.…”

Section: Speech Recognitionmentioning

confidence: 99%

Research of the coating textiles’ coating Gram weight measurement system based on infrared

Zhang¹,

Du²,

Liao³

2015

Advances in Engineering Materials and Applied Mechanics

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This paper proposes several speech technology improvements for increasing robustness, reliability and ergonomics in speech interfaces for controlling aerial vehicles. These improvements consist of including a statistical language model for increasing the robustness against spontaneous speech, incorporating confidence measures for evaluating the performance of on-line the speech engines (better reliability), and a flexible response generation for improving the interface ergonomics. This paper includes a detailed description of the speech control interface developed as a result of the collaboration between the GTH (Grupo de Tecnología del Habla or Speech Technology Group) at Universidad Politécnica de Madrid (UPM) and the company Boeing Research and Technology Europe under the contract No. 206/05. This interface includes modules that perform speech recognition, natural language understanding and response generation via a speech synthesizer. In the system evaluation, the final results reported a 96.4% Word Accuracy and a 92.2% Semantic Concept Accuracy. This paper also provides a state-of-art review of using Speech Technology for controlling aerial vehicles, comparing the main initiatives carried out. A significant conclusion of this work is that Speech Technology is now ready enough to be considered as a new modality (in parallel with traditional ones) for introducing high level commands while the controller is carrying out others actions when interacting with these control systems. In critical applications (such as this) the best performance of this technology is achieved when all the configuration possibilities of the speech engines are accessible and the speech interface is designed in collaboration with Speech Technology experts.

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Section: Speech Recognitionmentioning

confidence: 99%

Research of the coating textiles’ coating Gram weight measurement system based on infrared

Zhang¹,

Du²,

Liao³

2015

Advances in Engineering Materials and Applied Mechanics

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“…Recently, progress has been achieved in a number of particular domains of ASR including telephone speech [96], children's speech [220], noisy environments [58], speech emotion recognition [244] and meeting speech [23]. In the next subsection, we turn to the details of how an ASR system is built.…”

Section: The Scope and Variability Of Human Speechmentioning

confidence: 99%

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Larson

2012

FNT in Information Retrieval

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“…There are a variety of commercial and open-source toolkits available for automated speech recognition. Several major universities focus entire programs on the research and development of these tools [10,11,3] and this work has quickly found its way into commercial development by such notable firms as Microsoft and Nuance. This work is heavily utilized (but not extended) in this paper.…”

Section: Automated Speech Recognitionmentioning

confidence: 99%

“…Potential uses of these recordings include: Natural Language Understanding (NLU) Classifier Model Training [13], Speech Recognizer Model Training [10], Emotion Detection Model Training [6], Construction of Intelligent Agents [28], Speech Application Testing, Automated Feedback Loops & Machine Learning [28].…”

Section: Introductionmentioning

confidence: 99%

Protecting privacy in recorded conversations

Cunningham

Truta

2008

Proceedings of the 2008 International Workshop on Privacy and Anonymity in Information Society

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Professionals in the field of speech technology are often constrained by a lack of speech corpora that are important to their research and development activities. These corpora exist within the archives of various businesses and institutions; however, these entities are often prevented from sharing their data due to privacy rules and regulations. Efforts to "scrub" this data to make it shareable can result in data that has been either inadequately protected or data that has been rendered virtually unusable due to the loss resulting from suppression. This work attempts to address these issues by developing a scientific workflow that combines proven techniques in data privacy with controlled audio distortion resulting in corpora that have been adequately protected with minimal information loss.

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Automatic transcription of conversational telephone speech

Cited by 20 publications

References 28 publications

Research of the coating textiles’ coating Gram weight measurement system based on infrared

Research of the coating textiles’ coating Gram weight measurement system based on infrared

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Protecting privacy in recorded conversations

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