Speaker identity preservation dropped to about 20–30% in Hindi, down from roughly 35–45% in English, so the cloned voice largely lost its original character in cross-language generation.
What was measured
Voice Match Accuracy
Whether the generated voice actually sounds like the original speaker, including tone, pitch, rhythm, and identity.
decisive for this rankingtransformation
This ranking is fundamentally about whether the generated speech still sounds like the target speaker, so identity match is core. (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
Long-Form Consistency◐ MixedAt the generated clip length, the Hindi output stayed structurally stable, but the report did not test any longer Hindi passage.Multilingual Output Quality◐ MixedThe Hindi generation was intelligible and usable, but overall multilingual cloning quality was only fair because the voice no longer sounded much like the original speaker; the report also says results may need further tuning per language.Naturalness & Human Quality✓ WorkedThe Hindi output still sounded human-like with natural pauses rather than robotic.Pronunciation Accuracy✓ WorkedHindi pronunciation itself was accurate and clear on the generated output, despite the weaker speaker-identity match.
Provenance
- Observation
- a5504bab-bddd-476a-a3c2-d112f4c5e28a
- 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: "minimax-io",
scenario: "voice-cloning"
})MCP · mcp.aidemos.com/api/mcp
Free with attribution.
Same input, same check — 8 other tools
measured on Voice Match Accuracy
AICloneVoiceFree.com⚠ StruggledCross-language speaker identity preservation drops sharply in Hindi: the generated voice sounds noticeably different from the English reference output rather than retaining the same speaker identity well.ElevenLabs✗ 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.Fish Audio✓ WorkedRetains speaker identity across English-to-Hindi cloning: the Hindi output was judged a strong, consistent match to the tool's own English reference output, and the second Hindi render matched the first.Heygen◐ MixedThe Hindi clone preserved some of the original speaker's vocal characteristics, but it was not a close match overall when compared against the English best-variant reference output.Inworld⚠ StruggledIn Hindi, speaker identity dropped noticeably and was significantly off overall versus the English reference output, so cross-language voice preservation was weak.TopMediai Voice Cloning◐ MixedIn Hindi, HD preserves speaker identity inconsistently: some sections stay close to the original voice while others sound noticeably different.Uberduck✗ FailedThe Hindi output bore no real resemblance to the source speaker and was judged the weakest identity-preservation result in the set.VocalAI⚠ StruggledIn Hindi, the cloned voice preserved only about 15–20% of the original speaker's identity, with most of the output sounding significantly different from the source voice.
This evidence is published in
Real inputs and real outputs, no retouching · every cell queryable via API & MCP · aidemos.com