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Hits 1 – 18 of 18

1
H2, E2, ERK1 Children's Writing
Berkling, Kay. - : Linguistic Data Consortium, 2018. : https://www.ldc.upenn.edu, 2018
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2
H2, E2, ERK1 Children's Writing ...
Berkling, Kay. - : Linguistic Data Consortium, 2018
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3
H1 Children's Writing
Berkling, Kay. - : Linguistic Data Consortium, 2016. : https://www.ldc.upenn.edu, 2016
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4
H1 Children's Writing ...
Berkling, Kay. - : Linguistic Data Consortium, 2016
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5
Data Exploration of Sentence Structures and Embellishments in German texts: Comparing Children’s Writing vs Literature
Lavalley, Rémy [Verfasser]; Berkling, Kay [Verfasser]. - Hildesheim : Universitätsbibliothek Hildesheim, 2014
DNB Subject Category Language
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6
Data Exploration of Sentence Structures and Embellishments in German texts: Comparing Children’s Writing vs Literature
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7
Automatische Analyse von Rechtschreibfähigkeit auf Basis von Speech-Processing-Technologien ...
Fay, Johanna; Berkling, Kay; Stüker, Sebastian. - : Schneider-Verlag Hohengehren, 2012
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8
Automatische Analyse von Rechtschreibfähigkeit auf Basis von Speech-Processing-Technologien
In: Didaktik Deutsch : Halbjahresschrift für die Didaktik der deutschen Sprache und Literatur 17 (2012) 33, S. 14-36 (2012)
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9
Towards Context-dependent Phonetic Spelling Error Correction in Children's Freely Composed Text for Diagnostic and Pedagogical Purposes
Stüker, Sebastian; Fay, Johanna; Berkling, Kay. - : Curran Associates, Inc., 2011
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10
Synthesis of child speech with HMM adaptation and voice conversion
In: Institute of Electrical and Electronics Engineers. IEEE transactions on audio, speech and language processing. - New York, NY : Inst. 18 (2010) 5, 1005-1016
BLLDB
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11
Synthesis of Child Speech With HMM Adaptation and Voice Conversion
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12
HMM Adaptation and Voice Conversion for the Synthesis of Child Speech: A Comparison
Abstract: This study compares two different methodologies for producing data-driven synthesis of child speech from existing systems that have been trained on the speech of adults. On one hand, an existing statistical parametric synthesiser is transformed using model adaptation techniques, informed by linguistic and prosodic knowledge, to the speaker characteristics of a child speaker. This is compared with the application of voice conversion techniques to convert the output of an existing waveform concatenation synthesiser with no explicit linguistic or prosodic knowledge. In a subjective evaluation of the similarity of synthetic speech to natural speech from the target speaker, the HMM-based systems evaluated are generally preferred, although this is at least in part due to the higher dimensional acoustic features supported by these techniques.
URL: http://hdl.handle.net/1842/3923
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13
HMM-based synthesis of child speech
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14
Automatic language identification
In: Speech communication. - Amsterdam [u.a.] : Elsevier 35 (2001) 1, 115-124
OLC Linguistik
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15
SCoPE, syllable core and periphery evaluation: Automatic syllabification and foreign accent identification
In: Speech communication. - Amsterdam [u.a.] : Elsevier 35 (2001) 1, 125-138
OLC Linguistik
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16
SCoPE, Syllable Core and Periphery Evaluation: Automatic Syllabification and Application to Foreign Accent Identification
In: DTIC (2000)
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17
Automatic Language Identification
In: DTIC (2000)
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18
Automatic Language Identification with Sequences of Language-Independent Phoneme Clusters.
In: DTIC AND NTIS (1996)
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