Related to the Problem of Word Formation in German

The problem of word production, together with its many models, forms, and styles of expression. This article investigates the challenges surrounding the development of words in German, as well as the viewpoints of a number of scientists who have dealt with these topics. Concurrently, the categorization of these things in accordance with the semantic principle is being spoken about as well

Vowel classification based approach for Telugu Text-to-Speech System using symbol concatenation

Telugu is one of the oldest languages in India. This paper describes the development of Telugu Text-to-Speech System (TTS) using vowel classification. Vowels are most important class of sound in most Indian languages. The duration of vowel is longer than consonants and is most significant. Here vowels are categorized as starting middle and end according to the position of occurrence in a word. The algorithm developed by us involves analysis of a sentence in terms of words and then symbols involving combination of pure consonants and vowels. Wave files are being merged as per the requirement to generate the modified consonants influenced by deergalu (vowel sign) and yuktaksharas generate the speech from a text. Speech unit database consisting of vowels (starting, middle and end) and consonants is developed. We evaluated our TTS using Mean Opinion Score (MOS) for intelligibility and voice quality with and without using vowel classification from sixty five listeners, and got better results with vowel classification

A Context-based Numeral Reading Technique for Text to Speech Systems

This paper presents a novel technique for context based numeral reading in Indian language text to speech systems. The model uses a set of rules to determine the context of the numeral pronunciation and is being integrated with the waveform concatenation technique to produce speech out of the input text in Indian languages. For this purpose, the three Indian languages Odia, Hindi and Bengali are considered. To analyze the performance of the proposed technique, a set of experiments are performed considering different context of numeral pronunciations and the results are compared with existing syllable-based technique. The results obtained from different experiments shows the effectiveness of the proposed technique in producing intelligible speech out of the entered text utterances compared to the existing technique even with very less storage and execution time

Text to Speech Conversion for Odia Language

Text-to-Speech (TTS) system is designed to generate natural and intelligible sounding speech from any arbitrary input Odia digital text. The arbitrary text can be generated from a corresponding image file that undergoes processing through an Optical Character Recognition (OCR) scheme. This project is a research work on various techniques viable to develop the segmentation phase of the OCR specifically and a corresponding TTS for Odia language. The pre-processing and segmentation phases of the OCR are thoroughly explored in our work. A scheme is contrived for extracting the atomic Odia characters from a given string of text consisting of both characters and matras. The concept of histograms has come handy in our research. An altogether new L-corner scheme is formulated to handle the exceptional cases. Extensive simulations are carried out to validate the efficacy of the proposed algorithm. Results show that the proposed scheme attains a high level of accuracy. The methodology used in TTS is to exploit acoustic representations of speech for synthesis, together with linguistic analyses of text to extract correct pronunciations and prosody in context of Odia language. Phonetic analysis to convert grapheme to phoneme is achieved using an array numbering system for the audio files comprising of pre-recorded natural human speech. Concatenation of phones and diphones generates the speech. The phoneme database creation studying the prosody of Odia language is our primary focus in this project apart from accurate and intelligible speech generation