Voices

ttsforge uses Kokoro TTS which provides 54 high-quality neural voices across 9 languages.

Voice Naming Convention

Voices follow a consistent naming pattern:

{language}{gender}_{name}

Where:

Language: Two-letter code (af, am, bf, etc.)
Gender: f = female, m = male
Name: Voice identifier

For example:

af_heart = American English, Female, “Heart” voice
am_adam = American English, Male, “Adam” voice
bf_emma = British English, Female, “Emma” voice

Listing Voices

List all available voices:

ttsforge voices

List voices for a specific language:

ttsforge voices -l a  # American English
ttsforge voices -l b  # British English

Voice Demo

Listen to all voices:

# All voices in one file
ttsforge demo

# Specific language
ttsforge demo -l a

# Save individual files
ttsforge demo --separate -o ./voice_samples/

Voices by Language

American English (a)

Female Voices (11):

Voice	Description	Default
`af_alloy`	Versatile, balanced voice
`af_aoede`	Clear, pleasant tone
`af_bella`	Warm, friendly voice
`af_heart`	Expressive, emotional voice	Yes
`af_jessica`	Professional, articulate
`af_kore`	Youthful, energetic voice
`af_nicole`	Soft, gentle voice
`af_nova`	Modern, dynamic voice
`af_river`	Calm, flowing voice
`af_sarah`	Confident, clear voice
`af_sky`	Light, airy voice

Male Voices (9):

Voice	Description	Notes
`am_adam`	Deep, authoritative voice	Popular for audiobooks
`am_echo`	Resonant, clear voice
`am_eric`	Friendly, approachable voice
`am_fenrir`	Strong, dramatic voice
`am_liam`	Young, energetic voice
`am_michael`	Professional narrator voice
`am_onyx`	Deep, smooth voice
`am_puck`	Playful, expressive voice
`am_santa`	Warm, jolly voice	Seasonal character voice

British English (b)

Female Voices (4):

Voice	Description	Default
`bf_alice`	Elegant, refined voice
`bf_emma`	Classic British voice	Yes
`bf_isabella`	Sophisticated voice
`bf_lily`	Gentle, soft voice

Male Voices (4):

Voice	Description	Notes
`bm_daniel`	Traditional British voice
`bm_fable`	Storytelling voice	Great for narratives
`bm_george`	Authoritative, mature voice
`bm_lewis`	Modern British voice

Spanish (e)

Female Voices (1):

Voice	Description	Default
`ef_dora`	Clear Spanish voice	Yes

Male Voices (2):

Voice	Description	Notes
`em_alex`	Natural Spanish voice
`em_santa`	Warm Spanish voice	Seasonal

French (f)

Female Voices (1):

Voice	Description	Default
`ff_siwis`	Natural French voice	Yes

Hindi (h)

Female Voices (2):

Voice	Description	Default
`hf_alpha`	Clear Hindi voice	Yes
`hf_beta`	Alternative Hindi voice

Male Voices (2):

Voice	Description	Notes
`hm_omega`	Deep Hindi voice
`hm_psi`	Natural Hindi voice

Italian (i)

Female Voices (1):

Voice	Description	Default
`if_sara`	Natural Italian voice	Yes

Male Voices (1):

Voice	Description	Notes
`im_nicola`	Clear Italian voice

Japanese (j)

Female Voices (4):

Voice	Description	Default
`jf_alpha`	Standard Japanese voice	Yes
`jf_gongitsune`	Storytelling voice
`jf_nezumi`	Soft Japanese voice
`jf_tebukuro`	Gentle Japanese voice

Male Voices (1):

Voice	Description	Notes
`jm_kumo`	Natural Japanese male voice

Brazilian Portuguese (p)

Female Voices (1):

Voice	Description	Default
`pf_dora`	Natural Portuguese voice	Yes

Male Voices (2):

Voice	Description	Notes
`pm_alex`	Clear Portuguese voice
`pm_santa`	Warm Portuguese voice	Seasonal

Mandarin Chinese (z)

Female Voices (4):

Voice	Description	Default
`zf_xiaobei`	Northern accent
`zf_xiaoni`	Soft Chinese voice
`zf_xiaoxiao`	Popular Chinese voice	Yes
`zf_xiaoyi`	Clear Chinese voice

Male Voices (4):

Voice	Description	Notes
`zm_yunjian`	Strong male voice
`zm_yunxi`	Natural male voice
`zm_yunxia`	Youthful male voice
`zm_yunyang`	Mature male voice

Voice Blending

Combine multiple voices for unique narration. You can specify voice blends in two ways:

Using –voice parameter (recommended):

The --voice parameter now auto-detects blend format when you include colons and commas:

# 50/50 blend of two voices
ttsforge convert book.epub --voice "af_nicole:50,am_michael:50"

# Weighted blend (70% Nicole, 30% Michael)
ttsforge convert book.epub --voice "af_nicole:70,am_michael:30"

# Works with sample command
ttsforge sample "Hello world" --voice "af_sky:60,bf_emma:40" -p

# Works with phonemes preview
ttsforge phonemes preview "Test" --voice "am_adam:50,am_michael:50" --play

Using –voice-blend parameter (traditional):

# Explicit voice-blend parameter
ttsforge convert book.epub --voice-blend "af_nicole:50,am_michael:50"

# Can combine with regular voice (blend takes precedence)
ttsforge convert book.epub --voice af_sky --voice-blend "af_nicole:60,am_michael:40"

Voice blending creates a mixed voice by interpolating the voice embeddings. This can create interesting narrator voices, but results may vary. Blending works best with voices of the same language and similar characteristics.

Recommendations

For Audiobooks (Fiction)

American English: af_heart (female), am_adam (male)
British English: bf_emma (female), bm_fable (male)

For Audiobooks (Non-Fiction)

American English: af_sarah (female), am_michael (male)
British English: bf_alice (female), bm_george (male)

For Technical Content

Clear articulation: af_jessica, am_eric
Moderate speed: Use -s 0.95 for complex content

For Children’s Books

Expressive voices: af_kore, am_puck
Storytelling voices: bf_emma, bm_fable

Language Code Reference

Code	Language	Voices	Default Voice
`a`	American English	20	`af_heart`
`b`	British English	8	`bf_emma`
`e`	Spanish	3	`ef_dora`
`f`	French	1	`ff_siwis`
`h`	Hindi	4	`hf_alpha`
`i`	Italian	2	`if_sara`
`j`	Japanese	5	`jf_alpha`
`p`	Brazilian Portuguese	3	`pf_dora`
`z`	Mandarin Chinese	8	`zf_xiaoxiao`