Text-to-speech (TTS) is the generation ofsynthesized speech from text.Language is the ability to express one’sthoughts by means of a set of signs (text), gestures,and sounds. It is a distinctive feature of humanbeings, who are the only creatures to use such asystem. Speech is the oldest means of communicationbetween people and it is also the most widely used.‘Speech synthesis’ also called ‘Text to speechsynthesis’ is the artificial production ofhuman speech. A computer system used for thispurpose is called a speech synthesizer and can beimplemented in software. A text-to-speech(TTS) system converts text to speech.The proposed Enhanced Transcriptions Method is developed using Microsoft Visual Studio in VB.Net Language. Firstly word indexing is performed for the predefined words then corresponding speech signal is detected and errors in words are calculated using Euclidean distance. The results of the proposed work shows that Enhanced Transcriptions Method has more accuracy 89% as compared to previous Transcriptions Method 79%. The value of specificity for proposed method is 0.89 and for previous method is 0.79.
Improving Trajectory Modelling for DNN-Based Speech Synthesis by Using Stacked Bottleneck Features and Minimum Generation Error Training