Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Domain Adaptation of low-resource Target-Domain models using
  well-trained ASR Conformer Models   In this paper, we investigate domain adaptation for low-resource Automatic
Speech Recognition (ASR) of target-domain data, when a well-trained ASR model
trained with a large dataset is available. We argue that in the encoder-decoder
framework, the decoder of the well-trained ASR model is largely tuned towards
the source-domain, hurting the performance of target-domain models in vanilla
transfer-learning. On the other hand, the encoder layers of the well-trained
ASR model mostly capture the acoustic characteristics. We, therefore, propose
to use the embeddings tapped from these encoder layers as features for a
downstream Conformer target-domain model and show that they provide significant
improvements. We do ablation studies on which encoder layer is optimal to tap
the embeddings, as well as the effect of freezing or updating the well-trained
ASR model's encoder layers. We further show that applying Spectral Augmentation
(SpecAug) on the proposed features (this is in addition to default SpecAug on
input spectral features) provides a further improvement on the target-domain
performance. For the LibriSpeech-100-clean data as target-domain and SPGI-5000
as a well-trained model, we get 30% relative improvement over baseline.
Similarly, with WSJ data as target-domain and LibriSpeech-960 as a well-trained
model, we get 50% relative improvement over baseline.

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The categories of this paper are: stat
23
The categories of this paper are: solv-int
31
The categories of this paper are: ao-sci
18
The categories of this paper are: econ
7
The categories of this paper are: hep-th
29
The categories of this paper are: funct-an
17
The categories of this paper are: q-fin
33
The categories of this paper are: plasm-ph
32
The categories of this paper are: atom-ph
9
The categories of this paper are: nlin
24
The categories of this paper are: dg-ga
14
The categories of this paper are: math-ph
35
The categories of this paper are: mtrl-th
34
The categories of this paper are: chem-ph
5
The categories of this paper are: gr-qc
0
The categories of this paper are: hep-ph