Model reference · open weights
xun_tal_zh_adult_teach_branchformer is an open-weight audio or speech model from espnet. AxForge deploys and operates it for you on dedicated EU-owned hardware — with the licence handled where one is required.
Available as managed deployment — configured and operated for you on dedicated EU hardware, quoted per deployment.
What it is
| Maker | espnet |
|---|---|
| Type | Audio & music |
| Task | Speech→text |
| Runs with | espnet |
| Released | 2025-12-17 |
| Popularity | 9 downloads / month |
| Licence | Open weights |
About
espnet/xun_tal_zh_adult_teach_branchformerThis model was trained by Xun Gong using tal_zh_adult_teach recipe in espnet.
Follow the ESPnet installation instructions if you haven't done that already.
cd espnet
git checkout c61e21170895255cb93d1d3857bc15b818daca99
pip install -e .
cd egs2/tal_zh_adult_teach/asr1
./run.sh --skip_data_prep false --skip_train true --download_model espnet/xun_tal_zh_adult_teach_branchformer
Wed Dec 17 15:20:29 EST 20253.10.19 (main, Oct 21 2025, 16:43:05) [GCC 11.2.0]espnet2 202511pytorch 2.6.0+cu126c61e21170895255cb93d1d3857bc15b818daca99
Mon Dec 15 04:37:35 2025 -0800| dataset | Snt | Wrd | Corr | Sub | Del | Ins | Err | S.Err |
|---|---|---|---|---|---|---|---|---|
| decode_asr_branchformer_asr_model_valid.acc.ave/test | 6072 | 8500 | 38.8 | 59.1 | 2.1 | 1.3 | 62.5 | 78.6 |
| decode_asr_branchformer_lm_lm_train_lm_transformer_zh_char_valid.loss.ave_asr_model_valid.acc.ave/test | 6072 | 8500 | 38.9 | 59.2 | 1.8 | 1.7 | 62.8 | 78.5 |
| decode_asr_branchformer_asr_model_valid.acc.ave/org/dev | 3208 | 4291 | 41.2 | 56.3 | 2.5 | 1.6 | 60.5 | 72.8 |
| decode_asr_branchformer_lm_lm_train_lm_transformer_zh_char_valid.loss.ave_asr_model_valid.acc.ave/org/dev | 3208 | 4291 | 41.5 | 56.1 | 2.4 | 2.1 | 60.6 | 72.5 |
| dataset | Snt | Wrd | Corr | Sub | Del | Ins | Err | S.Err |
|---|---|---|---|---|---|---|---|---|
| decode_asr_branchformer_asr_model_valid.acc.ave/test | 6072 | 160057 | 89.4 | 8.2 | 2.4 | 0.9 | 11.4 | 78.6 |
| decode_asr_branchformer_lm_lm_train_lm_transformer_zh_char_valid.loss.ave_asr_model_valid.acc.ave/test | 6072 | 160057 | 89.2 | 8.2 | 2.7 | 1.1 | 11.9 | 78.5 |
| decode_asr_branchformer_asr_model_valid.acc.ave/org/dev | 3208 | 77334 | 91.3 | 7.2 | 1.5 | 0.8 | 9.6 | 72.8 |
| decode_asr_branchformer_lm_lm_train_lm_transformer_zh_char_valid.loss.ave_asr_model_valid.acc.ave/org/dev | 3208 | 77334 | 90.9 | 7.4 | 1.7 | 1.0 | 10.1 | 72.5 |
config: conf/train_asr_branchformer_e24_amp.yaml
print_config: false
log_level: INFO
drop_last_iter: false
dry_run: false
iterator_type: sequence
valid_iterator_type: null
output_dir: exp/asr_train_asr_branchformer_e24_amp_raw_zh_char_sp
ngpu: 1
seed: 0
num_workers: 4
num_att_plot: 3
dist_backend: nccl
dist_init_method: env://
dist_world_size: 4
dist_rank: 0
local_rank: 0
dist_master_addr: localhost
dist_master_port: 51233
dist_launcher: null
multiprocessing_distributed: true
unused_parameters: false
sharded_ddp: false
use_deepspeed: false
deepspeed_config: null
gradient_as_bucket_view: true
ddp_comm_hook: null
cudnn_enabled: true
cudnn_benchmark: false
cudnn_deterministic: true
use_tf32: false
collect_stats: false
write_collected_feats: false
max_epoch: 60
patience: null
val_scheduler_criterion:
- valid
- acc
early_stopping_criterion:
- valid
- loss
- min
best_model_criterion:
- - valid
- acc
- max
keep_nbest_models: 10
nbest_averaging_interval: 0
grad_clip: 5
grad_clip_type: 2.0
grad_noise: false
accum_grad: 1
no_forward_run: false
resume: true
train_dtype: float32
use_amp: true
log_interval: null
use_matplotlib: true
use_tensorboard: true
create_graph_in_tensorboard: false
use_wandb: false
wandb_project: null
wandb_id: null
wandb_entity: null
wandb_name: null
wandb_model_log_interval: -1
detect_anomaly: false
use_adapter: false
adapter: lora
save_strategy: all
adapter_conf: {}
pretrain_path: null
init_param: []
ignore_init_mismatch: false
freeze_param: []
num_iters_per_epoch: null
batch_size: 20
valid_batch_size: null
batch_bins: 25000000
valid_batch_bins: null
category_sample_size: 10
upsampling_factor: 0.5
category_upsampling_factor: 0.5
dataset_upsampling_factor: 0.5
dataset_scaling_factor: 1.2
max_batch_size: null
min_batch_size: 1
train_shape_file:
- exp/asr_stats_raw_zh_char_sp/train/speech_shape
- exp/asr_stats_raw_zh_char_sp/train/text_shape.char
valid_shape_file:
- exp/asr_stats_raw_zh_char_sp/valid/speech_shape
- exp/asr_stats_raw_zh_char_sp/valid/text_shape.char
batch_type: numel
valid_batch_type: null
fold_length:
- 51200
- 150
sort_in_batch: descending
shuffle_within_batch: false
sort_batch: descending
multiple_iterator: false
chunk_length: 500
chunk_shift_ratio: 0.5
num_cache_chunks: 1024
chunk_excluded_key_prefixes: []
chunk_default_fs: null
chunk_max_abs_length: null
chunk_discard_short_samples: true
train_data_path_and_name_and_type:
- - dump/raw/train_sp/wav.scp
- speech
- kaldi_ark
- - dump/raw/train_sp/text
- text
- text
valid_data_path_and_name_and_type:
- - dump/raw/dev/wav.scp
- speech
- kaldi_ark
- - dump/raw/dev/text
- text
- text
multi_task_dataset: false
allow_variable_data_keys: false
max_cache_size: 0.0
max_cache_fd: 32
allow_multi_rates: false
valid_max_cache_size: null
exclude_weight_decay: false
exclude_weight_decay_conf: {}
optim: adam
optim_conf:
lr: 0.001
weight_decay: 1.0e-06
scheduler: warmuplr
scheduler_conf:
warmup_steps: 35000
token_list:
-
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- 啊
-
- 我
- 们
- 就
- 了
- 那
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- 对
- 来
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- 呢
- 有
- 十
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- 么
- 二
- 吧
- 三
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- 分
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- 要
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- 在
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- 于
- 可
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- 到
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- 所
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- 上
- 等
- 哎
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- 面
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- 也
- 六
- 多
- 点
- 两
- 写
- 角
- 里
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- 他
- 家
- 把
- 方
- 出
- 然
- 都
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- 没
- 减
- 再
- 法
- 给
- 人
- 问
- 为
- 最
- 该
- 儿
- 和
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- 用
- 学
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- 百
- 八
- 果
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- 得
- 先
- 间
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- 接
- A
- 零
- 话
- 少
- 呀
- X
- 七
- 咱
- 过
- 子
- 九
- 实
- 怎
- 候
- 知
- 其
- 吗
- 中
- 种
- 直
- 派
- 变
- 求
- 老
- 式
- 意
- 正
- 很
- 位
- 度
- 只
- 几
- 音
- 号
- 赛
- B
- 自
- 师
- 形
- 行
- 因
- 除
- 常
- 关
- 平
- 相
- 解
- 当
- 些
- 完
- 友
- 朋
- 起
- 值
- 讲
- 倍
- 但
- 答
- 前
- 天
- 开
- 尔
- 长
- 特
- 非
- 嗯
- 根
- 着
- 阿
- 作
- 发
- 结
- 单
- 理
- 哪
- C
- 选
- 表
- 文
- 线
- 别
- 己
- 部
- 次
- 谁
- 画
- 刚
- 跟
- 考
- 记
- 系
- 回
- 字
- 叫
- 情
- 整
- 思
- 负
- 经
- 找
- 明
- 注
- 课
- 从
- 错
- 图
- 地
- K
- 又
- 扣
- 告
- 已
- 条
From the published model card. Full card on the HuggingFace links in the sidebar.
How it works
Using it via the API
Once AxForge deploys xun-tal-zh-adult-teach-branchformer for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (xun-tal-zh-adult-teach-branchformer below is illustrative; you get the exact model name on deployment.)
$ curl -sS https://api.axforge.ai/v1/audio/transcriptions \ -H "Authorization: Bearer $AXFORGE_API_KEY" \ -F model="xun-tal-zh-adult-teach-branchformer" -F file=@audio.mp3
Create an account — your API key is available in the console. 5M tokens/month currently included with every new account at launch.