Search Results - "Gopinath, Deepa P."

Complex Numbers and Rhythmic Changes by Geethamma, V. G., Gopinath, Deepa P., Daniel, Jacob K.

“…The concept of complex numbers (CNs) is used in many disciplines. In many cases, students find it difficult to understand the logic behind CNs. Rotations,…”
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Transfer learning for Speech Based Emotion Recognition by Nair, Meenu S, Gopinath, Deepa P

“…Speech emotion recognition has an important role in computer-mediated human communication. One of the major challenges in speech-based emotion recognition is…”
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Pause duration model for Malayalam TTS by James, Jesin, Gopinath, Deepa P.

“…In this paper a CART-based pause duration prediction model has been developed for Malayalam language. Prosodic features like pause durations, syllable…”
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Non-uniform unit selection using fuzzy ARTMAP for memory based Malayalam TTS by Thomas, Neethu, Gokul, P., Thomas, Crisil, Gopinath, Deepa P.

“…Text to speech synthesis system intended for any language, converts the given text in that language to corresponding speech. The major challenge in TTS system…”
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Synthesizing intonation for Malayalam TTS by Thomas, Crisil, Gokul, P., Thomas, Neethu, Gopinath, Deepa P.

“…In this paper we propose a new method for modeling intonation for Malayalam language Text To Speech (TTS) synthesis system. It is obtained by combining curve…”
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Analysis of the chaotic nature of speech prosody and music by Thomas, Abraham, Gopinath, Deepa P.

“…Speech and music prosody deals with the presence of rhythm. This work is the analysis of the presence of the chaotic nature in the duration patterns of speech…”
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ANN Based Classification of Unknown Genome Fragments Using Chaos Game Representation by Nair, Vrinda V, Vijayan, Karthika, Gopinath, Deepa P, Nair, Achuthsankar S

“…Classification of organisms into different categories using their genomic sequences has found importance in study of evolutionary characteristics, specific…”
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Advocating Character Error Rate for Multilingual ASR Evaluation by K, Thennal D, James, Jesin, Gopinath, Deepa P, K, Muhammed Ashraf

“…Automatic speech recognition (ASR) systems have traditionally been evaluated using English datasets, with the word error rate (WER) serving as the predominant…”
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IMaSC -- ICFOSS Malayalam Speech Corpus by Gopinath, Deepa P, K, Thennal D, Nair, Vrinda V, S, Swaraj K, G, Sachin

“…Modern text-to-speech (TTS) systems use deep learning to synthesize speech increasingly approaching human quality, but they require a database of high quality…”
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Entropy of Malayalam language and text compression using Huffman coding by Kuruvila, Melbin, Gopinath, Deepa P.

“…Entropy is a statistical parameter which measures how much information is produced on the average for each letter of a text in the language. Every language…”
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Modeling pause duration for Malayalam language TTS by James, Jesin, Gopinath, Deepa P.

“…Synthesized speech output from a Text To Speech (TTS) synthesis system requires the inclusion of prosodic features like pause durations, syllable prolongations…”
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Duration modeling for text to speech synthesis system using festival speech engine developed for Malayalam language by Rajan, Bindhu K., Rijoy, V., Gopinath, Deepa P., George, Nimmy

“…This paper describes duration modeling in Text To Speech Synthesis (TTS) for Malayalam language using open source Festival TTS engine. Classification and…”
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Clustering of duration patterns in speech for Text-to-Speech Synthesis by Sreelekshmi, K. S., Gopinath, Deepa P.

“…Synthesis of natural sounding speech is the greatest challenge in a Text-to-Speech Synthesis (TTS) system. In natural speech, duration, intensity and pitch are…”
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A hybrid duration model using CART and HMM by Gopinath, D.P., Vinod, C., Veena, S.G., Achuthsankar, S.N.

“…The duration of phoneme vary dynamically during continuous speech giving rhythm or prosody to speech. To make synthesized speech appear natural, the durational…”
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Duration Analysis for Malayalam Text-To-Speech Systems by Gopinath, D.P., Divya Sree, J., Mathew, R., Rekhila, S.J., Nair, A.S.

“…Naturalness can be achieved in a text-to-speech (TTMP) by incorporating prosodic features which include duration of basic units, intonation patterns and…”
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