SPEECH RECOGNITION USING RECURRENT NEURAL NETWORK AND CONVOLUTIONAL NEURAL NETWORK / (Kayıt no. 292842)
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| 000 -BAŞLIK | |
|---|---|
| Sabit Uzunluktaki Kontrol Alanı | 02716nam a22002657a 4500 |
| 003 - KONTROL NUMARASI KİMLİĞİ | |
| Kontrol Alanı | KOHA |
| 005 - EN SON İŞLEM TARİHİ ve ZAMANI | |
| Kontrol Alanı | 20241014092710.0 |
| 008 - SABİT UZUNLUKTAKİ VERİ ÖGELERİ - GENEL BİLGİ | |
| Sabit Alan | 240924d2024 cy d a|| |||| 00| 0 eng d |
| 040 ## - KATALOGLAMA KAYNAĞI | |
| Özgün Kataloglama Kurumu | CY-NiCIU |
| Kataloglama Dili | eng |
| Çeviri Kurumu | CY-NiCIU |
| Açıklama Kuralları | rda |
| 041 ## - DİL KODU | |
| Metin ya da ses kaydının dil kodu | eng |
| 090 ## - Yerel Tasnif No | |
| tasnif no | YL 3365 |
| Cutter no | A86 2024 |
| 100 1# - KİŞİ ADI | |
| Yazar Adı (Kişi adı) | Atosha, Pascal Bahavu |
| 245 10 - ESER ADI BİLDİRİMİ | |
| Başlık | SPEECH RECOGNITION USING RECURRENT NEURAL NETWORK AND CONVOLUTIONAL NEURAL NETWORK / |
| Sorumluluk Bildirimi | PASCAL BAHAVU ATOSHA ; SUPERVISOR, ASST. PROF. DR. EMRE ÖZBİLGE |
| 264 ## - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE | |
| Date of production, publication, distribution, manufacture, or copyright notice | 2024 |
| 300 ## - FİZİKSEL TANIMLAMA | |
| Sayfa, Cilt vb. | 69 sheets : |
| Boyutları | 30 cm |
| Birlikteki Materyal | +1 CD ROM |
| Diğer fiziki detaylar | illustrations, tables ; |
| 336 ## - CONTENT TYPE | |
| Source | rdacontent |
| Content type term | text |
| Content type code | txt |
| 337 ## - MEDIA TYPE | |
| Source | rdamedia |
| Media type term | unmediated |
| Media type code | n |
| 338 ## - CARRIER TYPE | |
| Source | rdacarrier |
| Carrier type term | volume |
| Carrier type code | nc |
| 502 ## - TEZ NOTU | |
| Tez Notu | Thesis (MSc) - Cyprus International University. Institute of Graduate Studies and Research Computer Engineering |
| 520 ## - ÖZET NOTU | |
| Özet notu | The Recent years have seen tremendous advancements in speech recognition<br/>technology, which has become essential to many different applications, such as virtual<br/>assistants and transcription services. In order to improve the precision and resilience<br/>of speech recognition systems, this thesis investigates the combined use of recurrent<br/>neural networks (RNNs) and convolutional neural networks (CNNs). The study starts<br/>with a thorough analysis of the state-of-the-art speech recognition models, stressing<br/>the advantages and disadvantages of CNNs and RNNs. CNNs are skilled at obtaining<br/>organized characteristics based on spectrogram representations, whereas RNNs are<br/>best at gathering temporal dependencies in sequential data. This study suggests a<br/>combination of models that brings together the sequential learning skills of RNNs<br/>alongside the spatial feature mining prowess of CNNs, driven by their complementary<br/>strengths. Common metrics such as word error rate, match error rate, word information<br/>lost, and word information preserved were used to evaluate the performance of our<br/>combined model.With 0.2476 of word error rate, 0.0732 match error rate, 0.36 of word<br/>information lost, and 0.53 of word information preserved, our system achieved these<br/>results. The results of this research add to the current debate on the development of<br/>speech recognition technology by presenting a new method for combining the<br/>advantages of RNNs and CNNs in a way that maximizes their mutually beneficial<br/>impacts. For applications requiring accurate and reliable speech-to-text conversion,<br/>the proposed combined model shows promise, as speech recognition remains an<br/>essential part of interaction between humans and computers. |
| 650 #0 - KONU BAŞLIĞI EK GİRİŞ - KONU TERİMİ | |
| Konusal terim veya coğrafi ad | Computer Engineering |
| Alt başlık biçimi | Dissertations, Academic |
| 700 1# - EK GİRİŞ - KİŞİ ADI | |
| Yazar Adı (Kişi adı) | Özbilge, Emre |
| İlişkili Terim | supervisor |
| 942 ## - EK GİRİŞ ÖGELERİ (KOHA) | |
| Sınıflama Kaynağı | Dewey Onlu Sınıflama Sistemi |
| Materyal Türü | Thesis |
| Geri Çekilme Durumu | Kayıp Durumu | Sınıflandırma Kaynağı | Kredi için değil | Koleksiyon Kodu | Kalıcı Konum | Mevcut Konum | Raf Yeri | Kayıt Tarih | Source of acquisition | Toplam Ödünçverme | Yer Numarası | Demirbaş Numarası | Son Görülme Tarihi | Kopya Bilgisi | Fatura Tarihi | Materyal Türü | Genel / Bağış Notu |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Dewey Onlu Sınıflama Sistemi | Tez Koleksiyonu | CIU LIBRARY | CIU LIBRARY | Depo | 24.09.2024 | Bağış | YL 3365 A86 2024 | T3782 | 24.09.2024 | C.1 | 24.09.2024 | Thesis | Computer Engineering | ||||
| Dewey Onlu Sınıflama Sistemi | Tez Koleksiyonu | CIU LIBRARY | CIU LIBRARY | Görsel İşitsel | 24.09.2024 | Bağış | YL 3365 A86 2024 | CDT3782 | 24.09.2024 | C.1 | 24.09.2024 | Suppl. CD | Computer Engineering |