5.6 Para-/Non-Linguistic Feature Preservation

Our findings show that the proposed approach can preserve paralinguistic information during trans-
lation. The original speaker’s voice is preserved to a high degree, as shown in Tab.4. Tab.4
reports the average similarity scores for the test set. For the baseline, we use a TTS system
and pick speakers randomly. A Higher score is better, where 0 corresponds to no correlation,
1 corresponds to the same vector, and -1 is an opposing vector. A value of 0.6 shows that
there is a good correlation between input and output speaker identities. The baseline values of

9

Table 3: Comparison of supervised and un-
supervised approaches on the CVSS dataset.
1Results from Jia et al. [2022b], 2results from
Inaguma et al. [2022], and TranSpeech results
are based on Huang et al. [2022a].

Approach

En → Es

Es → En

SMOS BLEU SMOS BLEU

Unsupervised
Baseline
Proposed
Supervised
T11
T21
Cascaded1
TranSpeech
S2TT+TTS2
S2UT2
UnitY2

4.08
4.03

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-
-
-
-
-
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Translatotron3