SARCASM IN SYNTHETIC SPEECH: EVALUATING ELEVENLABS’ TTS PROSODY FOR PRAGMATICS INSTRUCTION
DOI:
https://doi.org/10.22460/eltin.v14i2.p359-372Keywords:
Sarcasm, Prosody, Text-to-speech, Acoustic features, PragmaticsAbstract
This study examines how sarcasm is acoustically signaled by text-to-speech (TTS) and human encoders by analyzing key acoustic parameters including mean fundamental frequency (F0), F0 SD, F0 range, mean amplitude, amplitude range, and speech rate. The study compares sarcasm encoding in ElevenLabs, a commercially available advanced TTS model, and native American English speakers. A total of twelve encoders participated in the study, consisting of six TTS voices from ElevenLabs and six native American English speakers recruited through Fiverr. The dataset comprises 240 recordings, with each encoder generating both sincere and sarcastic versions of the same sentences. Acoustic parameters were extracted using Praat and computed using descriptive statistics and Linear Mixed Models (LMMs). The results reveal that sarcasm is consistently associated with reduced pitch, pitch variability, and slower speech rate, while amplitude does not differentiate significantly between attitudes. Subsequently, differences between TTS and human encoders are not uniform, which indicates that the TTS model approximates general prosodic patterns but differs in the magnitude of how these features are signaled. Overall, the findings suggest that TTS presents a partial approximation of human sarcastic prosody, capturing general acoustic patterns while remaining limited in expressive variability in sarcastic contexts.
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