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The Domain Mismatch Problem in the Broadcast Speaker Attribution Task
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In: Applied Sciences ; Volume 11 ; Issue 18 (2021)
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| 2 |
Albayzin 2018 Evaluation: The IberSpeech-RTVE Challenge on Speech Technologies for Spanish Broadcast Media
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In: Applied Sciences ; Volume 9 ; Issue 24 (2019)
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| 3 |
An Analysis of the Short Utterance Problem for Speaker Characterization
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In: Applied Sciences ; Volume 9 ; Issue 18 (2019)
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| 4 |
Supervector Extraction for Encoding Speaker and Phrase Information with Neural Networks for Text-Dependent Speaker Verification
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In: Applied Sciences ; Volume 9 ; Issue 16 (2019)
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| 5 |
Study of time and frequency variability in pathological speech and error reduction methods for automatic speech recognition
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In: http://dihana.cps.unizar.es/~alborada/docu/interspeech.pdf (2006)
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| 6 |
AV@CAR: A spanish multichannel multimodal corpus for in-vehicle automatic audio-visual speech recognition
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In: http://www.lrec-conf.org/proceedings/lrec2004/pdf/389.pdf (2004)
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Abstract:
This paper describes the acquisition of the multichannel multimodal database AV@CAR for automatic audio-visual speech recognition in cars. Automatic speech recognition (ASR) plays an important role inside vehicles to keep the driver away from distraction. It is also known that visual information (lip-reading) can improve accuracy in ASR under adverse conditions as those within a car. The corpus described here is intended to provide training and testing material for several classes of audiovisual speech recognizers including isolated word system, word-spotting systems, vocabulary independent systems, and speaker dependent or speaker independent systems for a wide range of applications. The audio database is composed of seven audio channels including, clean speech (captured using a close talk microphone), noisy speech from several microphones placed on the overhead of the cabin, noise only signal coming from the engine compartment and information about the speed of the car. For the video database, a small video camera sensible to the visible and the near infrared bands is placed on the windscreen and used to capture the face of the driver. This is done under different light conditions both during the day and at night. Additionally, the same individuals are recorded in laboratory, under controlled environment conditions to obtain noise free speech signals, 2D images and 3D + texture face models. 1.
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URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.666.9558
http://www.lrec-conf.org/proceedings/lrec2004/pdf/389.pdf
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| 7 |
Using APL2 to Compute the Dimension of a Fractal Represented as a Grammar,” APL Quote Quad 30
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In: http://www.apl-online.de/Berlin2000/VP036.PDF (2000)
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| 8 |
Using APL2 to Compute the Dimension of a Fractal Represented as a Grammar
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In: http://www.ii.uam.es/~alfonsec/docs/apl2000b.ps (2000)
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