Mere account mein kitna balance hai? -- On building voice enabled Banking Services for Multilingual Communities
This work addresses the need for accessible banking services in rural, multilingual settings, though it is incremental as it applies existing methods to a new domain.
The paper tackled the problem of building voice-enabled banking services for multilingual communities by developing speech-based intent recognition systems that handle code mixing and filled pauses, achieving results using a Naive Bayes classifier on acoustic phone units.
Tremendous progress in speech and language processing has brought language technologies closer to daily human life. Voice technology has the potential to act as a horizontal enabling layer across all aspects of digitization. It is especially beneficial to rural communities in scenarios like a pandemic. In this work we present our initial exploratory work towards one such direction -- building voice enabled banking services for multilingual societies. Speech interaction for typical banking transactions in multilingual communities involves the presence of filled pauses and is characterized by Code Mixing. Code Mixing is a phenomenon where lexical items from one language are embedded in the utterance of another. Therefore speech systems deployed for banking applications should be able to process such content. In our work we investigate various training strategies for building speech based intent recognition systems. We present our results using a Naive Bayes classifier on approximate acoustic phone units using the Allosaurus library.