TTS Arena — Klassifikazzjoni tal-Mudell tal-Vuċi AI
Qabbel 20+ mudelli test-to-speech. Benchmarks uffiċjali, klassifikazzjonijiet tal-komunità, u tqabbil naħa b'naħa.
Tqabbil naħa b'naħa
Ittajpja t-test, agħżel żewġ mudelli, u qabbel ir-riżultati. Mudelli b'saff ħieles ma jeħtieġu l-ebda kont.
Mudelli ħielsa jaħdmu mingħajr kont. Irreġistra issa biex tqabbel mudelli premium.
Mudell tal-Klassifika
| # | Mudell | Uffiċjali | Il-Komunità | Il-klassifikazzjoni tiegħek | Veloċità | Annimali |
|---|---|---|---|---|---|---|
| 1 |
Kokoro
Lightweight 82M parameter model delivering studio-quality speech with blazing-fast inference.
82M
1200h
2024
|
4.8 /5 |
5.0
/5
1 vot
|
fast | Free | |
| 2 |
CosyVoice 2
Alibaba's scalable streaming TTS with human-parity naturalness and near-zero latency.
300M
200000h
2024
|
4.26 /5 | L-ebda vot għadu | medium | Standard | |
| 3 |
Chatterbox
State-of-the-art zero-shot voice cloning with emotion control from Resemble AI.
300M
2025
|
4.25 /5 | L-ebda vot għadu | medium | Premium | |
| 4 |
StyleTTS 2
Human-level text-to-speech through style diffusion and adversarial training.
100M
585h
2024
|
4.23 /5 | L-ebda vot għadu | medium | Premium | |
| 5 |
Piper
A fast, local neural text to speech system optimized for Raspberry Pi and embedded devices.
15M
2023
|
4.15 /5 | L-ebda vot għadu | fast | Free | |
| 6 |
MeloTTS
High-quality multilingual text-to-speech that runs on CPU with minimal latency.
25M
2024
|
4.13 /5 | L-ebda vot għadu | fast | Free | |
| 7 |
Dia TTS
Multi-speaker dialog generation model that creates natural conversations between speakers.
1.6B
2024
|
4.09 /5 | L-ebda vot għadu | medium | Standard | |
| 8 |
VITS
Conditional variational autoencoder with adversarial learning for end-to-end text-to-speech.
25M
585h
2021
|
4.0 /5 | L-ebda vot għadu | fast | Free | |
| 9 |
Orpheus
Human-level emotional TTS model trained on 100K hours of speech data.
3B
100000h
2025
|
4.0 /5 | L-ebda vot għadu | medium | Standard | |
| 10 |
OpenVoice
Instant voice cloning with granular control over style, emotion, and accent.
300M
2024
|
4.0 /5 | L-ebda vot għadu | medium | Premium | |
| 11 |
IndexTTS-2
Zero-shot TTS with fine-grained emotion control and high expressiveness.
300M
2025
|
3.91 /5 | L-ebda vot għadu | medium | Standard | |
| 12 |
Spark TTS
Voice cloning TTS with controllable emotion and speaking style via prompts.
500M
2025
|
3.9 /5 | L-ebda vot għadu | medium | Standard | |
| 13 |
Parler TTS
Describe the voice you want in natural language and Parler generates matching speech.
880M
45000h
2024
|
3.83 /5 | L-ebda vot għadu | medium | Standard | |
| 14 |
Tortoise TTS
Multi-voice text-to-speech focused on quality with autoregressive architecture.
400M
50000h
2022
|
3.7 /5 | L-ebda vot għadu | slow | Premium | |
| 15 |
Bark
Transformer-based text-to-audio model that generates realistic speech, music, and sound effects.
350M
100000h
2023
|
3.57 /5 | L-ebda vot għadu | slow | Standard | |
| 16 |
Bark Small
Lighter version of Bark with faster inference and lower memory usage.
150M
100000h
2023
|
— | L-ebda vot għadu | medium | Standard | |
| 17 |
GLM-TTS
Achieves the lowest character error rate among open-source TTS models.
300M
2025
|
— | L-ebda vot għadu | medium | Standard | |
| 18 |
GPT-SoVITS
Few-shot voice cloning TTS that replicates any voice from just 5 seconds of audio.
200M
2024
|
— | L-ebda vot għadu | slow | Standard | |
| 19 |
Qwen3 TTS
Alibaba's multilingual TTS with voice cloning, preset voices, and voice design from text.
1.7B
2025
|
— | L-ebda vot għadu | medium | Standard | |
| 20 |
Sesame CSM
Conversational speech model generating natural dialogue with appropriate timing and emotion.
1B
2025
|
— | L-ebda vot għadu | slow | Premium | |
| 21 |
Chatterbox Turbo
Faster Chatterbox with sub-200ms latency and paralinguistic tags for laughs, coughs, and more.
350M
2025
|
— | L-ebda vot għadu | fast | Standard | |
| 22 |
Dia 2
Streaming-first conversational TTS with multi-speaker dialogue and paralinguistic cues.
2B
2025
|
— | L-ebda vot għadu | fast | Standard | |
| 23 |
VoxCPM
Tokenizer-free TTS producing 44.1kHz audio with context-aware paragraph consistency.
500M
1800000h
2025
|
— | L-ebda vot għadu | fast | Standard | |
| 24 |
OuteTTS
LLM-based TTS that runs on CPU, GPU, or browser via llama.cpp and Transformers.js.
1B
5000h
2025
|
— | L-ebda vot għadu | fast | Free | |
| 25 |
TADA
Zero-hallucination TTS with text-acoustic dual alignment, 5x faster than comparable LLM TTS.
1B
2026
|
— | L-ebda vot għadu | fast | Standard | |
| 26 |
VibeVoice
Microsoft's multi-speaker long-form TTS generating up to 90 minutes with 4 distinct speakers.
1.5B
100000h
2025
|
— | L-ebda vot għadu | fast | Standard | |
| 27 |
Pocket TTS
Lightweight 100M parameter model by Kyutai with voice cloning from a single sample.
100M
50000h
2025
|
— | L-ebda vot għadu | fast | Free | |
| 28 |
Kitten TTS
Ultra-lightweight TTS under 80MB. Runs on CPU without GPU.
80M
2025
|
— | L-ebda vot għadu | fast | Free | |
| 29 |
CosyVoice3
Next-generation multilingual TTS with bi-streaming, emotion control, and zero-shot voice cloning.
500M
200000h
2025
|
— | L-ebda vot għadu | fast | Standard | |
| 30 |
MOSS-TTS
Ultra-long 20-language TTS supporting up to 1 hour of continuous generation with phoneme-level control.
8B
500000h
2026
|
— | L-ebda vot għadu | medium | Premium | |
| 31 |
MegaTTS3
ByteDance's sparse alignment TTS with adjustable intelligibility vs. speaker similarity.
1B
100000h
2025
|
— | L-ebda vot għadu | slow | Premium |
Punteġġi dettaljati tal-Punteġġ Referenzjarju
Uffiċjali TTS.ai punteġġi benchmark madwar tliet dimensjonijiet: naturalezza, preċiżjoni, u l-veloċità.
Kokoro
Free
CosyVoice 2
Standard
Chatterbox
Premium
StyleTTS 2
Premium
Piper
Free
MeloTTS
Free
Dia TTS
Standard
VITS
Free
Orpheus
Standard
OpenVoice
Premium
IndexTTS-2
Standard
Spark TTS
Standard
Parler TTS
Standard
Tortoise TTS
Premium
Bark
Standard
Metodoloġija ta’ Referenza
Issettjar tat-test
- Hardware: 4x NVIDIA Tesla P40 (24GB VRAM kull wieħed), 96GB totali
- Test tat-test: 5 passaġġi standardizzati li jkopru mudelli differenti ta’ diskors (narrazzjoni, djalogu, tekniku, emozzjonali, multilingwi)
- Evalwazzjoni: Metriċi awtomatizzati (stima tal-MOS, WER, RTF) flimkien ma’ testijiet ta’ smigħ uman
- Runs: Kull mudell ittestjat 10 darbiet għal kull passaġġ, punteġġi medji
Kriterji ta’ punteġġ
- Naturalità (40%): Prożodija, intonazzjoni, ritmu, emozzjoni — kemm huma umani dawn il-ħsejjes?
- Preċiżjoni (30%): Il-korrettezza tal-pronunzja, ir-rata ta’ żbalji fil-kelma, l-intelliġibbiltà
- Veloċità (30%): Fattur tal-ħin reali (sekondi awdjo / sekondi tal-ġenerazzjoni). Ogħla = aktar mgħaġġel.
- B’mod ġenerali: Medja peżata: 0.4 x Naturalità + 0.3 x Preċiżjoni + 0.3 x Veloċità
Nota: Il-parametri referenzjarji jirriflettu l-prestazzjoni fuq il-ħardwer u t-testi tat-test speċifiċi tagħna. Il-kwalità fid-dinja reali tista' tvarja skont it-test tal-input, il-lingwa u l-għażla tal-vuċi.
Mistoqsijiet Frekwenti (FAQ)
X'nistgħu ntejbu? Il-feedback tiegħek jgħinna nsolvu l-problemi.
Sib il-vuċi perfetta tiegħek
Ipprova kwalunkwe mudell b'xejn ma Kokoro, Piper, VITS, jew MeloTTS. L-ebda kont meħtieġ.