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2015 - 201922020 - 20211
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Bölüm: Işık Üniversitesi, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü × Konu: Speech ×

Arama Sonuçları

Listeleniyor 1 - 3 / 3
  • Küçük Resim
    Yayın
    Chunking in Turkish with conditional random fields
    (Springer-Verlag, 2015-04-14) Yıldız, Olcay Taner; Solak, Ercan; Ehsani, Razieh; Görgün, Onur
    In this paper, we report our work on chunking in Turkish. We used the data that we generated by manually translating a subset of the Penn Treebank. We exploited the already available tags in the trees to automatically identify and label chunks in their Turkish translations. We used conditional random fields (CRF) to train a model over the annotated data. We report our results on different levels of chunk resolution.
  • Küçük Resim
    Yayın
    A multilayer annotated corpus for Turkish
    (IEEE, 2018-06-06) Yıldız, Olcay Taner; Ak, Koray; Ercan, Gökhan; Topsakal, Ozan; Asmazoğlu, Cengiz
    In this paper, we present the first multilayer annotated corpus for Turkish, which is a low-resourced agglutinative language. Our dataset consists of 9,600 sentences translated from the Penn Treebank Corpus. Annotated layers contain syntactic and semantic information including morphological disambiguation of words, named entity annotation, shallow parse, sense annotation, and semantic role label annotation.
  • Küçük Resim
    Yayın
    Improved microphone array design with statistical speaker verification
    (Elsevier Ltd, 2021-04) Demir, Kadir Erdem; Eskil, Mustafa Taner
    Conventional microphone array implementations aim to lock onto a source with given location and if required, tracking it. It is a challenge to identify the intended source when the location of the source is unknown and interference exists in the same environment. In this study we combine speaker verification and microphone array processing techniques to localize and maximize gain on the intended speaker under the assumption of open acoustic field. We exploit the steering capability of the microphone array for more accurate speaker verification. Our first contribution is a new N-Gram based and computationally efficient feature for detecting an intended speaker. When the source and interference are localized, microphone array can be tuned further to reduce noise and increase the gain. Our second contribution is this integrated algorithm for speaker verification and localization. In the context of this study we developed SharpEar, an open source environment that simulates propagation of sound emanating from multiple sources. Our third and last contribution is this simulation environment, which is open source and available to researchers of the field.