Becomes less consistent over longer Hindi passages, with quality fluctuations becoming more noticeable than in the English runs.
What was measured
Long-Form Consistency
Whether voice quality, pacing, and pronunciation stay consistent over longer passages instead of degrading after a few sentences.
decisive for this rankingtransformation
For text-to-voiceover work, the voice must stay stable across longer scripts; degradation means the output is not reliable. (3 of 3 judges)
What was given, what came back
Test input: Multilingual Voice Sample (Hindi) · text · group: voice-cloning
Input — what we sent
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Multilingual Voice Sample (Hindi)
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Multilingual Voice Sample (Hindi)
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Multilingual Voice Sample (Hindi)
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Multilingual Voice Sample (Hindi)
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Multilingual Voice Sample (Hindi)
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Multilingual Voice Sample (Hindi)
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Multilingual Voice Sample (Hindi)
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Multilingual Voice Sample (Hindi)
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Multilingual Voice Sample (Hindi)
A Hindi-language generation prompt applied to the already-cloned voice to test cross-language speaker preservation, pronunciation accuracy, and multilingual consistency across tools.
Why this input is hard
- · Multilingual voice generation
- · Cross-language speaker preservation
- · Pronunciation accuracy in Hindi
- · Tone, pitch, and pacing consistency across languages
- · Long-form multilingual reliability
Output — unretouched
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Also checked on this input — same tool, 4 other criteria
Multilingual Output Quality◐ MixedCan generate Hindi speech, but the output shifts tone, pacing, and pitch enough that speaker identity preservation is weak and the clone is not suitable when the original voice matters.Naturalness & Human Quality✓ WorkedStill sounds natural, human-like, and pleasant in Hindi even though the cloned identity is weak.Pronunciation Accuracy✓ WorkedKeeps Hindi flow and pronunciation generally smooth, even though identity preservation is weak.Voice Match Accuracy✗ FailedSpeaker identity retention drops sharply in Hindi: the report says the clone is poor in Hindi and does not closely resemble the original speaker when compared against the English reference outputs.
Provenance
- Observation
- 921eab3c-274a-407a-b303-a4eba0dbec01
- Evidence run
- 46222c41-0046-41cc-bfaa-5f7ba6aa4933
- Study
- Clone Your Voice and Generate Voiceover from Text
- Research task
- 86ba42bx1
- Tested at
- not recorded
- Source
- first-party
- Evidence state
- verified
- Proof shown
- input + output shown
- Cost / latency
- not captured
- Repeat run
- not captured
- Tester
- not captured
The last three rows are honest blanks, not placeholders — our capture has no field for them yet.
Query this
get_evidence({
tool: "elevenlabs",
scenario: "voice-cloning"
})MCP · mcp.aidemos.com/api/mcp
Free with attribution.
Same input, same check — 6 other tools
measured on Long-Form Consistency
Heygen⚠ StruggledThe multilingual output was not reliable for long passages, and the report says quality degraded during extended speech.Inworld◐ MixedOver the longer Hindi passage, the output stayed reasonably usable, but the report still frames it as mainly suitable for general voice generation rather than exact identity preservation.MiniMax◐ MixedAt the generated clip length, the Hindi output stayed structurally stable, but the report did not test any longer Hindi passage.TopMediai Voice Cloning⚠ StruggledGen+ is not consistent for long-form Hindi content, and voice characteristics become less stable as the passage gets longer.Uberduck⚠ StruggledThe output was already too poor at the outset to judge whether quality would degrade further over length.VocalAI◐ MixedLong-form consistency was acceptable but not fully reliable, with occasional quality fluctuations that made the output better suited to shorter multilingual content than extended narration.
This evidence is published in
Real inputs and real outputs, no retouching · every cell queryable via API & MCP · aidemos.com