diff --git "a/app.py" "b/app.py"
--- "a/app.py"
+++ "b/app.py"
@@ -1 +1,81 @@
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torch.nn.utils.parametrizations.weight_norm.\")\n"]},{"output_type":"display_data","data":{"text/plain":["tokenizer_config.json:   0%|          | 0.00/181 [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"a563e753021a42109c8394df9dd8b276"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["vocab.json:   0%|          | 0.00/291 [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"c7ad99598eb943f9acc5fbc81bff9a48"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["special_tokens_map.json:   0%|          | 0.00/85.0 [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"fef2c6bb469c4f78903ca8495c21364e"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["preprocessor_config.json:   0%|          | 0.00/213 [00:00<?, 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SpeechT5Processor.from_pretrained(\"microsoft/speecht5_tts\")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":177,"referenced_widgets":["1777e7e2bb0042229ac2e411f30afc9d","65f64bd89e2d447699c74f8e511a700d","a1369dc3f1d54a2dbe11115d7943e217","ce1f1b299af040c3ba51ba48b2f4aec9","a4e3a81addd546b8bb6f2c84a0c48753","6238f603120e48d2821b4d5f81737c85","c3373b0770dd4772835f69398f42369a","4885f987ad68447c90328ac04fa42e8f","5fd0545e78344ea183573910c5250374","9c70e0e0f287484f867a9ab2d0e46eeb","e4504e70453f464d9aff800cc52c23f6","38299f1d8387491baf0ad101b62f4151","5218871fecde4ae5835a57681a7b1397","e2ddd927a92244e79332e06ed059aa65","1ef6fa0aa525431db17eaa38afca45ba","45466b75c3e1452b982b434d022fea67","6b99e7fe6359448fa235cf7ff51f9143","de088fdf920d45f0be32a2d4878e7632","b2ab464c3bdf416780267528a7e25e12","ea007290d0b84592b0925a33f7cb7aa6","ffda797bde284a868534b00d3e9f7cf5","16e923b870734da78bc7c7b1e9263f2b","2e859a122e7a4e80a0e769efe73d8f42","5b363c03a4654d0785232bf7ec67b932","fa4de05fb7f3447aa43c1b7731d39649","be88acb5c40a4d069e781a7b682d000f","4653058901e94c7abd33fed52a053ec6","7155918cc218487a8ec4ed9776392340","7e969c53d7c94fa3bcabd676e4818567","4f09e74f25e34542b49a9136fe8104b4","397e636ad5f441319dbebce4b9b52886","85ea68a3e51d482090d80cddf7562371","7dd8e7e0e9434f7ebb40bfbbf9923cc9","eb17197fa68b477aa42f2f3d5e8052ef","9b0ef0ef38e349c78be4a7a82bb022d8","b249629682194ae7867f03442b866187","8bb61d9a2ba249d288a5afdd53b4b72a","a4ef007ebd6d4bbb87b117c9594ff4c2","f1f2c8650ef24882b97c9d2d1b7c677a","207378e6326e4bcea67957b21c923b95","ad9b67f4292b410788a6a29f315ac6b2","73c74df917a04a45bfe05f3271ac3ead","d690807a6d4b4448a700b183c9a6c689","c99f327a388e490785c2e30593d4d8a0","f43587d4115d4deca1c324dd129230c3","e124f66a133b466ca8211a30051515e6","f2beee69f82241ee890a6d8c16a82718","7a4fa2e7bcf04d43b22ff2ff2b8fedef","1db3c86b6eb94fa5aa26d87feec926ee","628871b38054476897965826457764be","813ad4e34539455987fddcc9b4d9d351","cdf96f92acfb43dd80dcf16c043dab97","52043285b5774b2f9291a224f8d836f9","2a159db8a6134139bf647497dcacace0","a32645c0f7e94129a8b759f5e96faa4f"]},"id":"wr2xnoWeyekD","executionInfo":{"status":"ok","timestamp":1702986734840,"user_tz":-180,"elapsed":1421,"user":{"displayName":"Dark死","userId":"15256269229091554240"}},"outputId":"2e77feb9-18dc-41cf-9bcf-3ac69fd67075"},"execution_count":6,"outputs":[{"output_type":"display_data","data":{"text/plain":["preprocessor_config.json: 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?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"eb17197fa68b477aa42f2f3d5e8052ef"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["special_tokens_map.json:   0%|          | 0.00/234 [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"f43587d4115d4deca1c324dd129230c3"}},"metadata":{}}]},{"cell_type":"code","source":["model = SpeechT5ForTextToSpeech.from_pretrained(\"microsoft/speecht5_tts\").to(device)\n","vocoder = SpeechT5HifiGan.from_pretrained(\"microsoft/speecht5_hifigan\").to(device)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":145,"referenced_widgets":["e8c326e93f3e4a14bacfee1ce92aff6f","789b49d2ec0e438c8ec03980a9a94e34","d05555b2e1444ec2acfae9a4568a5009","48d72aa9f01f4c0da98610f4c7785bf8","cf6ad407836f493595e0b8135fbb4d52","301fae09588d42a7bfda5ceb7d4c12e2","37eb46957b0f473fa086d4cfb60c7ab5","3ba40cf4503b459e866e35ea19b23416","437746f5b89343d18f824ae1509632b1","b0557fcd08264a04b9c9452cda8df68b","ea431a04e02f4f18bcf520d8f687d4fc","f12dd2080ffd45908295b38bb7796303","c410d591ce914acbaa3c0abf4e8c8f8b","cb3a672b8c614a88bbcf77b27fe2a39c","2c62c42ad06b4d988078be1b95bed399","7100f90619984d9cbad067a0891bd66e","7356fe27e256471dab582e9b03ac2120","212ec0daef4e4046906c6dd30ab5d69b","0f53384f591f4ea6b6d4387aa02c8e3f","87cee16547c143b3b9fd60e98b611374","dad08f9817a34cc08a1dbf69cb0351fe","81dfacbdd6dc410eac5ed209513842b2","49a971905d1d4c9b982c6113fe44f841","cdd14a7238184f18b3c925da414409ff","83dfd6d11dcb4307aff6c0f377ff9e72","d78388a765cf408e9a3d3e28a505a277","e854cfa770b148d793c8fc07564a8bf8","f32ac1b5a09a42e1bb48f47553612b3b","ef622bc2b1574c4986fc2a011020906c","b8fb0a41115146f4b193d65816d12921","690f1f82c4eb4245935137814e72ef92","ef15a20795de487d873c491b56b3d515","42df9576e79d4a43a88652dbfe9da149","40468e7581b54c82bf840b757ee35aa8","d1708fffe1544925b54009a512db6e78","c97ce93a58a0461abcfe38e420f5a571","12e94594447246479ff83009ebdbb100","515722bed704463da9f9eb4392152f73","671c53dc2342473b8d6422f62ac333be","16efd977a5424f30b1008395217f6fca","62ea32ce2db04b4b9e6a470f102408f8","fc54985906af4aae82762e4f92246649","99c758e6c4574b238d2047730e69b095","a9ebc723f4f04874bcb61e5a94b94dda"]},"id":"2ptax5lAyeox","executionInfo":{"status":"ok","timestamp":1702986751991,"user_tz":-180,"elapsed":13727,"user":{"displayName":"Dark死","userId":"15256269229091554240"}},"outputId":"c4772878-5f0c-4d13-a8a9-dd6cfa8687f3"},"execution_count":7,"outputs":[{"output_type":"display_data","data":{"text/plain":["config.json: 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?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"40468e7581b54c82bf840b757ee35aa8"}},"metadata":{}}]},{"cell_type":"code","source":["embeddings_dataset = load_dataset(\"Matthijs/cmu-arctic-xvectors\", split=\"validation\")\n","speaker_embeddings = torch.tensor(embeddings_dataset[7306][\"xvector\"]).unsqueeze(0)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":145,"referenced_widgets":["3abaee7dad584c169abc3eece2dea2da","9d3539c6b37d4b2595d92da655a24272","cd82af2012b84218a8bb3c06c4527170","f7cc5f12ca6c443783f83ade9a4e0c1a","ad0866e2fb514355996fe402b7fab8de","2d3b8ce5921849bf9be6b6f36f61b777","545bdfd96fee415185f5d688ccdf7854","a29b8e13084d464088ccd531caa27fdc","37028e1541e64cfdb5e1eb708fd8b3b6","a122f495aca441e39fe08b4e7e89634e","37bff8b14eab4b248e06fc6dc982b76f","95b2cedcd4fb4027be79205da557e765","30954b8700724c9e80a696ae3e422230","aaca1dfaea9949d8b71d5965a06298bc","254aa680c07d48d99c7411395e06f2da","78f9dfb1352f4da285e497d4ded6b90d","7406b44c0550426f8d37f8cdf15289d0","0de17da5386b466bbe01bec16cd3d6c1","3a7c370ad8d74148b632ecec3d327b20","3fc0a5f80d17421690e56ece7d984adc","da0935ba443849c593b698de57126014","07f63b28c06f4fd781ff3bf67dac69fa","8432118245084adab6d5c554e8435445","a450a3f8fb2f415d947042243ab50e97","902cc1283ddb4486bcd12fc46c09e905","ebbb9759894e4cfaa85e128ea45ec2e4","8ffeefe6bafa4b25b780283794a58f01","6f791ca27e3b48a98bc746ecdb3d9b3c","87b4eea1ad3e4af7ba2e6e28b7ebe299","51be76ebfac146da9026f29dbcc790f0","c8afc711501a46b5895eaf4713d991a9","56ed3048f9c24960840db073cc5f54c1","db188df474474e9799562d0dd0c9f98f","c155e5af263f4a029b05e304a7a0c674","9f64af0001d7456eb1b6c7bf15b7029a","c8dbb1000ebf4856a648de0f0323a677","38bd6f116a1945a6929487d3f9c99097","6140696044634f24b4779559740aebe5","b0ee6e10d5bd4da1b4a45365a3b3ee7a","6a81b109c9e64270b0737bf22824817f","ac97c104d7114fa59175bb8a29558138","efc476abe68548449b9ccf2394923ef3","42ab02088a5b4eaca753eee4239cb0cf","359d1ce2d18c4dd8bd703f3c26e1e72b"]},"id":"N-rCd3ruyerH","executionInfo":{"status":"ok","timestamp":1702986781839,"user_tz":-180,"elapsed":29850,"user":{"displayName":"Dark死","userId":"15256269229091554240"}},"outputId":"7adca46a-acea-4946-de5c-d1b3418ab159"},"execution_count":8,"outputs":[{"output_type":"display_data","data":{"text/plain":["Downloading builder script:   0%|          | 0.00/1.36k [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"3abaee7dad584c169abc3eece2dea2da"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Downloading readme:   0%|          | 0.00/1.01k [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"95b2cedcd4fb4027be79205da557e765"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Downloading data:   0%|          | 0.00/17.9M [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"8432118245084adab6d5c554e8435445"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Generating validation split: 0 examples [00:00, ? examples/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"c155e5af263f4a029b05e304a7a0c674"}},"metadata":{}}]},{"cell_type":"code","source":["def translate(audio):\n","    outputs = asr_pipe(audio, max_new_tokens=256, generate_kwargs={\"task\": \"translate\"})\n","    return outputs[\"text\"]"],"metadata":{"id":"r3TeB40ayetU","executionInfo":{"status":"ok","timestamp":1702986781839,"user_tz":-180,"elapsed":6,"user":{"displayName":"Dark死","userId":"15256269229091554240"}}},"execution_count":9,"outputs":[]},{"cell_type":"code","source":["def synthesise(text):\n","    inputs = processor(text=text, return_tensors=\"pt\")\n","    speech = model.generate_speech(inputs[\"input_ids\"].to(device), speaker_embeddings.to(device), vocoder=vocoder)\n","    return speech.cpu()"],"metadata":{"id":"kEvx4eZEyevo","executionInfo":{"status":"ok","timestamp":1702986781839,"user_tz":-180,"elapsed":4,"user":{"displayName":"Dark死","userId":"15256269229091554240"}}},"execution_count":10,"outputs":[]},{"cell_type":"code","source":["def speech_to_speech_translation(audio):\n","    translated_text = translate(audio)\n","    synthesised_speech = synthesise(translated_text)\n","    synthesised_speech = (synthesised_speech.numpy() * 32767).astype(np.int16)\n","    return 16000, synthesised_speech"],"metadata":{"id":"OFLBWlZ1yex4","executionInfo":{"status":"ok","timestamp":1702986781839,"user_tz":-180,"elapsed":4,"user":{"displayName":"Dark死","userId":"15256269229091554240"}}},"execution_count":11,"outputs":[]},{"cell_type":"code","source":["title = \"Cascaded STST\"\n","description = \"\"\"\n","Demo for cascaded speech-to-speech translation (STST), mapping from source speech in any language to target speech in English. Demo uses OpenAI's [Whisper Base](https://huggingface.co/openai/whisper-base) model for speech translation, and Microsoft's\n","[SpeechT5 TTS](https://huggingface.co/microsoft/speecht5_tts) model for text-to-speech:\n","![Cascaded STST](https://huggingface.co/datasets/huggingface-course/audio-course-images/resolve/main/s2st_cascaded.png \"Diagram of cascaded speech to speech translation\")\n","\"\"\""],"metadata":{"id":"95VS-T8ayezx","executionInfo":{"status":"ok","timestamp":1702986781839,"user_tz":-180,"elapsed":4,"user":{"displayName":"Dark死","userId":"15256269229091554240"}}},"execution_count":12,"outputs":[]},{"cell_type":"code","source":["demo = gr.Blocks()\n","\n","mic_translate = gr.Interface(\n","    fn=speech_to_speech_translation,\n","    inputs=gr.Audio(source=\"microphone\", type=\"filepath\"),\n","    outputs=gr.Audio(label=\"Generated Speech\", type=\"numpy\"),\n","    title=title,\n","    description=description,\n",")\n","\n","file_translate = gr.Interface(\n","    fn=speech_to_speech_translation,\n","    inputs=gr.Audio(source=\"upload\", type=\"filepath\"),\n","    outputs=gr.Audio(label=\"Generated Speech\", type=\"numpy\"),\n","    examples=[[\"./example.wav\"]],\n","    title=title,\n","    description=description,\n",")\n","\n","with demo:\n","    gr.TabbedInterface([mic_translate, file_translate], [\"Microphone\", \"Audio File\"])\n","\n","demo.launch()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":366},"id":"djgNrV9gye1n","executionInfo":{"status":"error","timestamp":1702986782416,"user_tz":-180,"elapsed":580,"user":{"displayName":"Dark死","userId":"15256269229091554240"}},"outputId":"6fcf9b6c-1b01-4ad0-8761-9a0c3741c0d7"},"execution_count":13,"outputs":[{"output_type":"error","ename":"TypeError","evalue":"ignored","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)","\u001b[0;32m<ipython-input-13-eeaf5ed42ba7>\u001b[0m in \u001b[0;36m<cell line: 3>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      3\u001b[0m mic_translate = gr.Interface(\n\u001b[1;32m      4\u001b[0m     \u001b[0mfn\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mspeech_to_speech_translation\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 5\u001b[0;31m     \u001b[0minputs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mgr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mAudio\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msource\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"microphone\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"filepath\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      6\u001b[0m     \u001b[0moutputs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mgr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mAudio\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlabel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"Generated Speech\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"numpy\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      7\u001b[0m     \u001b[0mtitle\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtitle\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/usr/local/lib/python3.10/dist-packages/gradio/component_meta.py\u001b[0m in \u001b[0;36mwrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m    153\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    154\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 155\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mfn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    156\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    157\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0mwrapper\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mTypeError\u001b[0m: Audio.__init__() got an unexpected keyword argument 'source'"]}]}]}
\ No newline at end of file
+# -*- coding: utf-8 -*-
+"""app.ipynb
+
+Automatically generated by Colaboratory.
+
+Original file is located at
+    https://colab.research.google.com/drive/16MxXQeF3O0htL9eQ61aa6ZxnApGg9TKN
+"""
+
+import gradio as gr
+import numpy as np
+import torch
+import sentencepiece
+from google.colab import drive
+from datasets import load_dataset
+
+from transformers import pipeline, VitsModel, VitsTokenizer
+
+device = "cuda:0" if torch.cuda.is_available() else "cpu"
+
+#eng audio to text transformation
+asr_pipe = pipeline("automatic-speech-recognition", model="asapp/sew-d-tiny-100k-ft-ls100h", device=device)
+
+#eng text to rus text translation
+translation_pipe = pipeline("translation", model="facebook/wmt19-en-ru")
+
+#rus text to rus speech transformation
+vits_model = VitsModel.from_pretrained("facebook/mms-tts-rus")
+vits_tokanizer = tokenizer = VitsTokenizer.from_pretrained("facebook/mms-tts-rus")
+
+def transform_audio_to_speech_en(audio):
+    outputs = asr_pipe(audio, max_new_tokens=256, generate_kwargs={"task": "translate"})
+    return outputs["text"]
+
+def translator(text):
+  translated_text = translation_pipe(text)
+  return translated_text[0]['translation_text']
+
+def synthesise(translated_text):
+    translated_text = translator(translated_text)
+    inputs = vits_tokanizer(translated_text, return_tensors="pt")
+    with torch.no_grad():
+        speech = vits_model(**inputs).waveform
+    return speech.cpu()
+
+def speech_to_speech_translation(audio):
+    translated_text = transform_audio_to_speech_en(audio)
+    synthesised_speech = synthesise(translated_text)
+    synthesised_speech = (synthesised_speech.numpy() * 32767).astype(np.int16)
+    return 16000, synthesised_speech[0]
+
+title = "Cascaded STST"
+description = """
+Demo for cascaded speech-to-speech translation (STST), mapping from source speech in any language to target speech in English. Demo uses OpenAI's [Whisper Base](https://huggingface.co/openai/whisper-base) model for speech translation, and Microsoft's
+[SpeechT5 TTS](https://huggingface.co/microsoft/speecht5_tts) model for text-to-speech:
+![Cascaded STST](https://huggingface.co/datasets/huggingface-course/audio-course-images/resolve/main/s2st_cascaded.png "Diagram of cascaded speech to speech translation")
+"""
+
+demo = gr.Blocks()
+
+mic_translate = gr.Interface(
+    fn=speech_to_speech_translation,
+    inputs=gr.Audio(source="microphone", type="filepath"),
+    outputs=gr.Audio(label="Generated Speech", type="numpy"),
+    title=title,
+    description=description,
+)
+
+file_translate = gr.Interface(
+    fn=speech_to_speech_translation,
+    inputs=gr.Audio(source="upload", type="filepath"),
+    outputs=gr.Audio(label="Generated Speech", type="numpy"),
+    examples=[["./example.wav"]],
+    title=title,
+    description=description,
+)
+
+with demo:
+    gr.TabbedInterface([mic_translate, file_translate], ["Microphone", "Audio File"])
+
+demo.launch()
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