demo first commit

requirements.txt

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+wenet @ git+https://github.com/revdotcom/rev-wenet@feature/NERD-3007
+gradio==3.14.0

rev_app.py

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+# Copyright (c) 2022 Horizon Robotics. (authors: Binbin Zhang)
+#               2022 Chengdong Liang (liangchengdong@mail.nwpu.edu.cn)
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import gradio as gr
+import torch
+from wenet.cli.model import load_model
+
+
+
+def process_cat_embs(cat_embs):
+    device = "cpu"
+    cat_embs = torch.tensor(
+        [float(c) for c in cat_embs.split(',')]).to(device)
+    return cat_embs
+
+
+def download_rev_models():
+    # from huggingface_hub import hf_hub_download
+    # import joblib
+
+    # REPO_ID = "Revai/reginald"
+    # FILENAME = "sklearn_model.joblib"
+
+    # model = joblib.load(
+    #     hf_hub_download(repo_id=REPO_ID, filename=FILENAME)
+    # )
+    model_path = "/Users/natalie/NERD-2941/reginald/10.jit.zip"
+    units_path = "/Users/natalie/NERD-2941/reginald/tk.units.txt"
+    audio_path = "/Users/natalie/NERD-2941/rev-wenet/runtime/web/fdhc0_si1559.wav"
+    cat_embs = "1,0"
+    device = "cpu"
+    cat_embs = process_cat_embs
+    model = load_model(model_path, units_path)
+    return model
+
+model = download_rev_models()
+    
+
+def recognition(audio, style=0):
+    if audio is None:
+        return "Input Error! Please enter one audio!"
+    # NOTE: model supports 16k sample_rate
+
+    cat_embs = ','.join([str(s) for s in (1-style, style)])
+    cat_embs = process_cat_embs(cat_embs)
+    ans = model.transcribe(audio, cat_embs = cat_embs)
+
+    if ans is None:
+        return "ERROR! No text output! Please try again!"
+    txt = ans['text']
+    return txt
+
+
+# input
+inputs = [
+    gr.inputs.Audio(source="microphone", type="filepath", label='Input audio'),
+    gr.Slider(0, 1, value=0, label="Style", info="Choose between verbatim and NV"),
+]
+
+output = gr.outputs.Textbox(label="Output Text")
+
+text = "Reginald Demo"
+
+# description
+description = (
+    "This is a speech recognition demo that supports verbatim and non-verbatim transcription. Try recording an audio with disfluencies (ex: \'uh\', \'um\') and testing both transcription styles."  # noqa
+)
+
+article = (
+    "<p style='text-align: center'>"
+    "<a href='https://rev.com' target='_blank'>Github: Learn more about Rev</a>"  # noqa
+    "</p>")
+
+interface = gr.Interface(
+    fn=recognition,
+    inputs=inputs,
+    outputs=output,
+    title=text,
+    description=description,
+    article=article,
+    theme='huggingface',
+)
+
+interface.launch(enable_queue=True)