Add to ORKGBrindöpke C, Fink GA, Kummert F, Sagerer G. An HMM-Based Recognition System for Perceptive Relevant Pitch Movements of Spontaneous German Speech. In: International Conference on Spoken Language Processing. Vol 7. Sydney; 1998: 2895-2898
Hidden Markov Models (HMMs) provides an effective framework for the modeling of time-varying sequenc...
The subject of this paper is a rule corpus of approx.1500 phonetic rules that models segmental varia...
In this paper detectors for accents, phrase boundaries, and sentence modality are described which de...
Brindöpke C, Fink GA, Kummert F. A Comparative Study of HMM-Based Approaches for the Automatic Recog...
Natural language processing enables computer and machines to understand and speak human languages. S...
The paper assesses the capability of an HMM-based TTS system to produce German speech. The results a...
Brindöpke C, Schaffranietz B. An annotation system for melodic aspects of German spontaneous speech....
Speech recognition systems for languages with a rich inflectional morphology (like German) suffer fr...
Speech recognition systems for languages with a rich inflectional morphology (like German) suffer fr...
Some approaches for coping with the problem of recognition of spontaneous speech dialogues are prese...
In this paper we investigate the use of articulatory data for speech recognition. Recordings of the ...
Brindöpke C, Schaffranietz B. Ein Transkriptionssystem für die Sprachmelodie des Deutschen. Linguist...
International audienceIn this paper, hidden Markov models (HMM)-based vowel and consonant automatic ...
In this paper, we describe automatic speech recognition system where features extracted from human s...
International audienceThis article discusses the automatic recognition of Cued Speech in French base...
Hidden Markov Models (HMMs) provides an effective framework for the modeling of time-varying sequenc...
The subject of this paper is a rule corpus of approx.1500 phonetic rules that models segmental varia...
In this paper detectors for accents, phrase boundaries, and sentence modality are described which de...
Brindöpke C, Fink GA, Kummert F. A Comparative Study of HMM-Based Approaches for the Automatic Recog...
Natural language processing enables computer and machines to understand and speak human languages. S...
The paper assesses the capability of an HMM-based TTS system to produce German speech. The results a...
Brindöpke C, Schaffranietz B. An annotation system for melodic aspects of German spontaneous speech....
Speech recognition systems for languages with a rich inflectional morphology (like German) suffer fr...
Speech recognition systems for languages with a rich inflectional morphology (like German) suffer fr...
Some approaches for coping with the problem of recognition of spontaneous speech dialogues are prese...
In this paper we investigate the use of articulatory data for speech recognition. Recordings of the ...
Brindöpke C, Schaffranietz B. Ein Transkriptionssystem für die Sprachmelodie des Deutschen. Linguist...
International audienceIn this paper, hidden Markov models (HMM)-based vowel and consonant automatic ...
In this paper, we describe automatic speech recognition system where features extracted from human s...
International audienceThis article discusses the automatic recognition of Cued Speech in French base...
Hidden Markov Models (HMMs) provides an effective framework for the modeling of time-varying sequenc...
The subject of this paper is a rule corpus of approx.1500 phonetic rules that models segmental varia...
In this paper detectors for accents, phrase boundaries, and sentence modality are described which de...