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Found 10 papers, 0 papers with code
Automatic Speech Recognition for Irish: the ABAIR-ÉIST System
This paper describes ÉIST, automatic speech recogniser for Irish, developed as part of the ongoing ABAIR initiative, combining (1) acoustic models, (2) pronunciation lexicons and (3) language models into a hybrid system.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Low-resource speech recognition and dialect identification of Irish in a multi-task framework
This setting is then used to train a model with an E-branchformer encoder and the performance of both architectures are compared.
Towards End-to-End Spoken Grammatical Error Correction
This foundation model can be used to replace the whole framework or part of it, e. g., ASR and disfluency removal.
Zero-shot Audio Topic Reranking using Large Language Models
A key element for this process is highly rapid, flexible, search to support large archives, which in MVSE is facilitated by representing video attributes by embeddings.
Towards spoken dialect identification of Irish
Motivated by this, the present experiments investigate spoken dialect identification of Irish, with a view to incorporating such a system into the speech recognition pipeline.
Towards dialect-inclusive recognition in a low-resource language: are balanced corpora the answer?
ASR systems are generally built for the spoken 'standard', and their performance declines for non-standard dialects/varieties.
Adapting an ASR Foundation Model for Spoken Language Assessment
Additionally, these models have a tendency to skip disfluencies and hesitations in the output.
Can Generative Large Language Models Perform ASR Error Correction?
In this paper we investigate using ChatGPT, a generative LLM, for ASR error correction.
Adapting an Unadaptable ASR System
As speech recognition model sizes and training data requirements grow, it is increasingly common for systems to only be available via APIs from online service providers rather than having direct access to models themselves.
N-best T5: Robust ASR Error Correction using Multiple Input Hypotheses and Constrained Decoding Space
Error correction models form an important part of Automatic Speech Recognition (ASR) post-processing to improve the readability and quality of transcriptions.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
