# Choosing a voice

Kokoro ships 54 voices. The names encode a language and a gender (`af_heart` is American female, `bm_george` is British male), and the quality spread is large, so earmark annotates the list with Kokoro's own grades.

``` bash
earmark voices                    # graded, grouped by language
earmark voices --lang b           # British only
earmark voices --all              # including the ones graded D or worse
earmark audio paper.pdf --voice af_bella
```

    American English
      af_heart        A   female   (default)
      af_bella        A-  female
      af_nicole       B-  female
      am_michael      C+  male
      am_puck         C+  male

    British English
      bf_emma         B-  female

Voices Kokoro grades D or worse are hidden unless you pass `--all`. They are bad enough that listing them by default would only waste your time.


# Which one

Only two voices are graded A. `af_heart` is the default and `af_bella` the runner-up; `am_michael` or `am_puck` are the best male voices, and `bf_emma` the best British one. Everything below B- is noticeably worse on a long listen.


# Hear one

Reading a grade table tells you less than three seconds of your own text does, and the model is already on disk:

``` bash
earmark voices --try af_bella
earmark voices --try bf_emma --text "Whatever you like."
```

Set a favourite once with `earmark config`:

``` toml
voice = "af_bella"
speed = 1.1
```

A command-line flag always wins over the file, so a one-off stays a one-off.


# Speed

`--speed` takes 0.5 to 2.0, default 1.0. Speeding up in earmark is not the same as speeding up in the player. The model synthesizes at the requested rate, so the result is a voice talking faster rather than a recording played faster. Most podcast apps can do the other thing on top.


# Languages

The `--lang` filter on `earmark voices` takes a single-letter name prefix: `a` (American English), `b` (British English), `e`, `f`, `h`, `i`, `j`, `p`, `z`. The `--lang` flag on `audio` and `publish` is a different thing: a language code like `en-us` passed to the model.


# The `say` engine

`--engine say` uses macOS's built-in `say` instead of Kokoro. It is much faster and much worse, and it needs no model download. It is useful for checking that a long document chunks and encodes correctly before committing to a real render.


# More

Kokoro's [VOICES.md](https://huggingface.co/hexgrad/Kokoro-82M/blob/main/VOICES.md) has the full grade table with training-data volumes, and the [official demo Space](https://huggingface.co/spaces/hexgrad/Kokoro-TTS) lets you audition voices in a browser.

All flags: [`earmark voices`](../reference/voices.md).