import os os.system("pip install nemo_toolkit['all']") import gradio as gr import nemo.collections.asr as nemo_asr model = nemo_asr.models.EncDecCTCModel.from_pretrained( model_name="stt_en_quartznet15x5" ) def speech_file(x): # print(x) text = model.transcribe([f"{x}"]) # print(text) return text def speech_record(x): text = model.transcribe([f"{x}"]) return text css = """ .gradio-container { font-family: 'IBM Plex Sans', sans-serif; } .gr-button { color: white; border-color: black; background: black; } input[type='range'] { accent-color: black; } .dark input[type='range'] { accent-color: #dfdfdf; } .container { max-width: 730px; margin: auto; padding-top: 1.5rem; } .details:hover { text-decoration: underline; } .gr-button { white-space: nowrap; } .gr-button:focus { border-color: rgb(147 197 253 / var(--tw-border-opacity)); outline: none; box-shadow: var(--tw-ring-offset-shadow), var(--tw-ring-shadow), var(--tw-shadow, 0 0 #0000); --tw-border-opacity: 1; --tw-ring-offset-shadow: var(--tw-ring-inset) 0 0 0 var(--tw-ring-offset-width) var(--tw-ring-offset-color); --tw-ring-shadow: var(--tw-ring-inset) 0 0 0 calc(3px var(--tw-ring-offset-width)) var(--tw-ring-color); --tw-ring-color: rgb(191 219 254 / var(--tw-ring-opacity)); --tw-ring-opacity: .5; } .footer { margin-bottom: 45px; margin-top: 35px; text-align: center; border-bottom: 1px solid #e5e5e5; } .footer>p { font-size: .8rem; display: inline-block; padding: 0 10px; transform: translateY(10px); background: white; } .dark .footer { border-color: #303030; } .dark .footer>p { background: #0b0f19; } .prompt h4{ margin: 1.25em 0 .25em 0; font-weight: bold; font-size: 115%; } .animate-spin { animation: spin 1s linear infinite; } @keyframes spin { from { transform: rotate(0deg); } to { transform: rotate(360deg); } } #share-btn-container { display: flex; margin-top: 1.5rem !important; padding-left: 0.5rem !important; padding-right: 0.5rem !important; background-color: #000000; justify-content: center; align-items: center; border-radius: 9999px !important; width: 13rem; } #share-btn { all: initial; color: #ffffff;font-weight: 600; cursor:pointer; font-family: 'IBM Plex Sans', sans-serif; margin-left: 0.5rem !important; padding-top: 0.25rem !important; padding-bottom: 0.25rem !important; } #share-btn * { all: unset; } """ with gr.Blocks(css = css) as demo: gr.Markdown( """ # Speech to Text - NVIDIA Qaurtznet15x5 (English) QuartzNet is a Jasper-like network that uses separable convolutions and larger filter sizes. It has comparable accuracy to Jasper while having much fewer parameters. This particular model has 15 blocks each repeated 5 times. """) with gr.Tab("Audio File"): with gr.Row().style(equal_height=True): audio_input2 = gr.Audio(label="Audio File", type="filepath") text_output2 = gr.Textbox(label="Transcription", show_label=False) file_button = gr.Button("Transcribe") with gr.Tab("Record"): with gr.Row().style(equal_height=True): audio_input3 = gr.Audio(label="Input Audio", source="microphone", type="filepath") text_output3 = gr.Textbox(label="Transcription", show_label=False) rec_button = gr.Button("Transcribe") gr.HTML(''' ''') file_button.click(speech_file, inputs=audio_input2, outputs=text_output2) rec_button.click(speech_record, inputs=audio_input3, outputs=text_output3) demo.launch()