RETRACTED ARTICLE: Automatic speech recognition systems: A survey of discriminative techniques

Kaur, Amanpreet; Singh, Amitoj; Sachdeva, Rohit; Kukreja, Vinay

doi:10.1007/s11042-022-13645-x

Cited by 8 publications

(2 citation statements)

References 141 publications

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“…Data cleaning and annotation are vital steps in preparing the collected speech data for the training and evaluation of the Arabic ASR system [89]. These processes involve ensuring data quality, removing noise, and providing accurate transcriptions to create a reliable and effective ASR TABLE 4: The table provides valuable information about the currently accessible dataset suitable for Arabic speech recognition.…”

Section: B Data Cleaning and Annotationmentioning

confidence: 99%

Arabic Speech Recognition: Advancement and Challenges

Rahman,

Kabir,

Mridha

et al. 2024

IEEE Access

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Speech recognition is a captivating process that revolutionizes human-computer interactions, allowing us to interact and control machines through spoken commands. The foundation of speech recognition lies in understanding a given language's linguistic and textual characteristics. Although automatic speech recognition (ASR) systems flawlessly convert speech into text for various international languages, their implementation for Arabic remains inadequate. In this research, we diligently explore the current state of Arabic ASR systems and unveil the challenges encountered during their development. We categorize these challenges into two groups: those specific to the Arabic language and those that are more general. Additionally, we propose strategies to overcome these obstacles and emphasize the need for ASR architectures tailored to the Arabic language's unique grammatical and phonetic structure. In addition, we provide a comprehensive and explicit description of various feature extraction methods, language models, and acoustic models utilized in the Arabic ASR system.

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Section: B Data Cleaning and Annotationmentioning

confidence: 99%

Arabic Speech Recognition: Advancement and Challenges

Rahman,

Kabir,

Mridha

et al. 2024

IEEE Access

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“…1 Existing approaches to combat piracy, such as implementing digital rights management (DRM) technologies and legal actions, often involve complex and time-consuming procedures. 2,3 In this research, we propose a revolutionary method that enables the tracking of audio content to its source of piracy by employing cryptographically invisibly fingerprinted technology.…”

Section: Introductionmentioning

confidence: 99%

Tracking any audio content streamed or played anywhere to its origin or piracy

Chandrasekaran¹

2023

Int J Sci Rep

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Background: The unauthorized distribution and consumption of audio content have been on the rise in recent years, posing a significant threat to content creators and streaming partners. In this research, we proposed a revolutionary method that enables the tracking of audio content to its source of piracy by employing cryptographically invisibly fingerprinted technology. Methods: Our approach utilizes advanced cryptographic techniques to embed inaudible fingerprints within audio frames. These fingerprints serve as unique identifiers that can be traced back to the source of piracy. Our specialized software employs sophisticated algorithms to detect and extract these cryptographic fingerprints from the pirated audio content. The software then compares the extracted fingerprints with a database of authorized sources to determine the origin of the piracy event. Results: Through extensive testing and analysis, we have demonstrated the effectiveness of our proposed method in accurately tracking audio content to its source of piracy. Our software consistently detects and reports the source, location, and time of the piracy incidents within a matter of minutes. Conclusions: The research presented in this paper introduces a novel method for tracking audio content streamed or played over the internet to its source of piracy. By employing cryptographically invisibly fingerprinted technology, we can accurately detect and report piracy incidents within minutes, providing content creators and streaming partners with actionable information to combat piracy effectively.

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