Challenges of Accent and vowels for Sindhi Speech Recognition System

doi:10.30534/ijatcse/2021/621022021

Cited by 3 publications

(1 citation statement)

References 7 publications

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“…Therefore, the methods that have been used successfully in English cannot adequately handle languages that have rich morphology structure. Numerous studies, such as those by [14], [15], [3] and others, have focused on ASR for tonal languages, and African languages.…”

Section: A Asrmentioning

confidence: 99%

Towards Yoruba-Speaking Google Maps Navigation

Oyesanmi,

Olukanmi

2024

Preprint

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Advances in natural language processing (NLP) have made several technological interventions and services available to people in different languages. One such service is the Google Maps direction narration which provides real-time oral assistance to tourists, and visitors in a new or unknown location. Like most related assistive technologies, this service is primarily developed in the English language with support for some other Western languages over time, and the African languages are largely neglected. This paper seeks to leverage advances in NLP techniques and models in the design of a speech-to-speech (STS) translation of the Google Maps direction narration in English to the Yoruba language, one of the most widely spoken languages in Western Africa. We begin with an exploration of various state-of-the-art NLP techniques for Automatic Speech Recognition (ASR), Machine Translation (MT), and Text-to-speech (TTS) models that make up the designed system. We presented the performance of the models we explored towards the design and implementation of a robust STS translation of the Google Maps direction narration in the Yoruba language.

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Section: A Asrmentioning

confidence: 99%

Towards Yoruba-Speaking Google Maps Navigation

Oyesanmi,

Olukanmi

2024

Preprint

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Thinning of Balti Script : Way Forward to Balti OCR

Dil Nawaz Hakro,

Abdul Majid,

Muhammad Nadeem

et al. 2024

Int. J. Sci. Res. Comput. Sci. Eng. Inf. Technol

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Natural language is one of the applications of Artificial Intelligence, which trains machines to do the jobs in human language. OCR is one of the fields where the writing efforts are omitted and text images are converted into editable text. An OCR may have post and preprocessing to enhance the text image more suitable for the rest of the OCR process. Thinning is the preprocessing approach in which the characters, words and text is thinned to its one-pixel skeleton. Much of the work has been done in the various languages of the world as well as Pakistani languages. The work on Balti OCR is nonexistent. In this study, a thinning algorithm is proposed for the Balti language, a language spoken in the northern areas of Pakistan and India. Many of the Balti images were tested with the proposed algorithm and the proposed system produced accurate results by giving a one pixel skeleton of input image. The proposed algorithm tested with hundreds of Balti language images and selected results are presented in this paper. The current research has many directions including the way forward to building Balti OCR, Balti ICR (both segmentation based and segmentation free).

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Balochi Text Segmentation for Establishing Balochi OCR

Muhammad Mazhar,

Qinbo,

Dil Nawaz Hakro

et al. 2024

Int. J. Sci. Res. Comput. Sci. Eng. Inf. Technol

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OCR is considered the fastest way of data entry; the smart conversion of the text data is called handwritten text recognition. Many of the languages possess OCRs and there are still some languages lacking the OCR. Balochi is one of the national languages of the Pakistan country and the most of speakers live in Baluchistan province of Pakistan. Balochi computing is at its infancy and require attention to its many of the approaches to accumulate the level of other languages especially pertaining to the matter of computation. This paper investigates the relation between other Arabic adopting languages and proposes a segmentation algorithm to segment Balochi text paragraphs into lines, lines into words and words into characters. The algorithm has been adopted and fine tuned to produce the accuracy of 95%. The segmentation algorithm will play a role in developing a complex OCR and handwritten recognition of Balochi language.

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Challenges of Accent and vowels for Sindhi Speech Recognition System

Cited by 3 publications

References 7 publications

Towards Yoruba-Speaking Google Maps Navigation

Towards Yoruba-Speaking Google Maps Navigation

Thinning of Balti Script : Way Forward to Balti OCR

Balochi Text Segmentation for Establishing Balochi OCR

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