Efficiently Detecting User-Defined Keywords in Text Using an Audio-Compliant Encoder
Main Ideas:
- Traditionally, spotting user-defined or flexible keywords in text involves using a costly text encoder alongside an audio encoder for joint analysis.
- This approach can lead to issues such as heterogeneous modality representation and increased complexity.
- A new architecture is proposed in this work that efficiently detects arbitrary keywords based on an audio-compliant text encoder.
- The audio-compliant text encoder has a homogeneous representation with audio embedding and is much smaller than a compatible text encoder.
- The proposed text encoder converts the text to phonemes using a specific method.
Author’s Take:
The traditional approach to spotting user-defined or flexible keywords in text using a text encoder can be expensive and complex. However, this article introduces a novel architecture that efficiently detects arbitrary keywords using an audio-compliant text encoder. This not only solves the issues of heterogeneous representation and increased complexity but also provides a smaller and more streamlined solution compared to a compatible text encoder. By converting text to phonemes, this new approach offers a promising way to improve keyword detection in text.