import{s as Z,o as ee,n as te}from"../chunks/scheduler.cd324960.js";import{S as ne,i as oe,e as p,s as h,c as j,h as ae,a as f,d as n,b as u,f as W,g as z,j as y,k as X,l as se,m as o,n as A,t as D,o as G,p as F,q as O,r as R}from"../chunks/index.d5c3adcc.js";import{T as ie}from"../chunks/Tip.889bec11.js";import{C as re,H as le,E as ce}from"../chunks/MermaidChart.svelte_svelte_type_style_lang.481f2bec.js";function he(C){let i,r,b="requirements.txt",g,s,x="transformers",l,c,m="<code>git+https://github.com/hollance/transformers.git@6900e8ba6532162a8613d2270ec2286c3f58f57b</code>";return{c(){i=O(`In our experience experimenting with the Dutch language, using an MMS TTS checkpoint results in better performance than a
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    If you decide to use an MMS TTS checkpoint, you will need to update the `),r=p("a"),r.textContent=b,g=O(`
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    fine-tuned SpeechT5 one, but you might find that your fine-tuned TTS checkpoint is preferable in your language.
    If you decide to use an MMS TTS checkpoint, you will need to update the `),r=f(a,"A",{href:!0,"data-svelte-h":!0}),y(r)!=="svelte-l0vtp8"&&(r.textContent=b),g=R(a,`
    file of your demo to install `),s=f(a,"CODE",{"data-svelte-h":!0}),y(s)!=="svelte-olzpwg"&&(s.textContent=x),l=R(a,` from the PR branch:
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audio applications. As you’ve experienced, building more involved audio tools is fully within reach by using the
foundational skills you’ve acquired in this course.`,d,v,B=`The hands-on exercise takes one of the applications covered in this Unit, and extends it with a few multilingual
tweaks 🌍 Your objective is to take the <a href="https://huggingface.co/spaces/course-demos/speech-to-speech-translation" rel="nofollow">cascaded speech-to-speech translation Gradio demo</a>
from the first section in this Unit, and update it to translate to any <strong>non-English</strong> language. That is to say, the
demo should take speech in language X, and translate it to speech in language Y, where the target language Y is not
English. You should start by <a href="https://huggingface.co/spaces/course-demos/speech-to-speech-translation?duplicate=true" rel="nofollow">duplicating</a>
the template under your Hugging Face namespace. There’s no requirement to use a GPU accelerator device - the free CPU
tier works just fine 🤗 However, you should ensure that the visibility of your demo is set to <strong>public</strong>. This is required
such that your demo is accessible to us and can thus be checked for correctness.`,H,_,K=`Tips for updating the speech translation function to perform multilingual speech translation are provided in the
section on <a href="speech-to-speech">speech-to-speech translation</a>. By following these instructions, you should be able
to update the demo to translate from speech in language X to text in language Y, which is half of the task!`,L,w,V=`To synthesise from text in language Y to speech in language Y, where Y is a multilingual language, you will need
to use a multilingual TTS checkpoint. For this, you can either use the SpeechT5 TTS checkpoint that you fine-tuned
in the previous hands-on exercise, or a pre-trained multilingual TTS checkpoint. There are two options for pre-trained
checkpoints, either the checkpoint <a href="https://huggingface.co/sanchit-gandhi/speecht5_tts_vox_nl" rel="nofollow">sanchit-gandhi/speecht5_tts_vox_nl</a>,
which is a SpeechT5 checkpoint fine-tuned on the Dutch split of the <a href="https://huggingface.co/datasets/facebook/voxpopuli" rel="nofollow">VoxPopuli</a>
dataset, or an MMS TTS checkpoint (see section on <a href="../chapter6/pre-trained_models">pretrained models for TTS</a>).`,P,T,E,$,J=`Your demo should take as input an audio file, and return as output another audio file, matching the signature of the
<a href="https://huggingface.co/spaces/course-demos/speech-to-speech-translation/blob/3946ba6705a6632a63de8672ac52a482ab74b3fc/app.py#L35" rel="nofollow"><code>speech_to_speech_translation</code></a>
function in the template demo. Therefore, we recommend that you leave the main function <code>speech_to_speech_translation</code>
as is, and only update the <a href="https://huggingface.co/spaces/course-demos/speech-to-speech-translation/blob/a03175878f522df7445290d5508bfb5c5178f787/app.py#L24" rel="nofollow"><code>translate</code></a>
and <a href="https://huggingface.co/spaces/course-demos/speech-to-speech-translation/blob/a03175878f522df7445290d5508bfb5c5178f787/app.py#L29" rel="nofollow"><code>synthesise</code></a>
functions as required.`,q,k,N=`Once you have built your demo as a Gradio demo on the Hugging Face Hub, you can submit it for assessment. Head to the
Space <a href="https://huggingface.co/spaces/huggingface-course/audio-course-u7-assessment" rel="nofollow">audio-course-u7-assessment</a> and
provide the repository id of your demo when prompted. This Space will check that your demo has been built correctly by
sending a sample audio file to your demo and checking that the returned audio file is indeed non-English. If your demo
works correctly, you’ll get a green tick next to your name on the overall <a href="https://huggingface.co/spaces/MariaK/Check-my-progress-Audio-Course" rel="nofollow">progress space</a> ✅`,Y,M,I,S,U;return s=new re({props:{containerStyle:"float: right; margin-left: 10px; display: inline-flex; position: relative; z-index: 10;"}}),l=new le({props:{title:"Hands-on exercise",local:"hands-on-exercise",headingTag:"h1"}}),T=new ie({props:{$$slots:{default:[he]},$$scope:{ctx:C}}}),M=new ce({props:{source:"https://github.com/huggingface/audio-transformers-course/blob/main/chapters/en/chapter7/hands_on.mdx"}}),{c(){i=p("meta"),r=h(),b=p("p"),g=h(),j(s.$$.fragment),x=h(),j(l.$$.fragment),c=h(),m=p("p"),m.textContent=a,d=h(),v=p("p"),v.innerHTML=B,H=h(),_=p("p"),_.innerHTML=K,L=h(),w=p("p"),w.innerHTML=V,P=h(),j(T.$$.fragment),E=h(),$=p("p"),$.innerHTML=J,q=h(),k=p("p"),k.innerHTML=N,Y=h(),j(M.$$.fragment),I=h(),S=p("p"),this.h()},l(e){const t=ae("svelte-u9bgzb",document.head);i=f(t,"META",{name:!0,content:!0}),t.forEach(n),r=u(e),b=f(e,"P",{}),W(b).forEach(n),g=u(e),z(s.$$.fragment,e),x=u(e),z(l.$$.fragment,e),c=u(e),m=f(e,"P",{"data-svelte-h":!0}),y(m)!=="svelte-5fgwkf"&&(m.textContent=a),d=u(e),v=f(e,"P",{"data-svelte-h":!0}),y(v)!=="svelte-1vndh8y"&&(v.innerHTML=B),H=u(e),_=f(e,"P",{"data-svelte-h":!0}),y(_)!=="svelte-1xc515h"&&(_.innerHTML=K),L=u(e),w=f(e,"P",{"data-svelte-h":!0}),y(w)!=="svelte-e3qygk"&&(w.innerHTML=V),P=u(e),z(T.$$.fragment,e),E=u(e),$=f(e,"P",{"data-svelte-h":!0}),y($)!=="svelte-r6bgbz"&&($.innerHTML=J),q=u(e),k=f(e,"P",{"data-svelte-h":!0}),y(k)!=="svelte-xkt7xj"&&(k.innerHTML=N),Y=u(e),z(M.$$.fragment,e),I=u(e),S=f(e,"P",{}),W(S).forEach(n),this.h()},h(){X(i,"name","hf:doc:metadata"),X(i,"content",pe)},m(e,t){se(document.head,i),o(e,r,t),o(e,b,t),o(e,g,t),A(s,e,t),o(e,x,t),A(l,e,t),o(e,c,t),o(e,m,t),o(e,d,t),o(e,v,t),o(e,H,t),o(e,_,t),o(e,L,t),o(e,w,t),o(e,P,t),A(T,e,t),o(e,E,t),o(e,$,t),o(e,q,t),o(e,k,t),o(e,Y,t),A(M,e,t),o(e,I,t),o(e,S,t),U=!0},p(e,[t]){const Q={};t&2&&(Q.$$scope={dirty:t,ctx:e}),T.$set(Q)},i(e){U||(D(s.$$.fragment,e),D(l.$$.fragment,e),D(T.$$.fragment,e),D(M.$$.fragment,e),U=!0)},o(e){G(s.$$.fragment,e),G(l.$$.fragment,e),G(T.$$.fragment,e),G(M.$$.fragment,e),U=!1},d(e){e&&(n(r),n(b),n(g),n(x),n(c),n(m),n(d),n(v),n(H),n(_),n(L),n(w),n(P),n(E),n($),n(q),n(k),n(Y),n(I),n(S)),n(i),F(s,e),F(l,e),F(T,e),F(M,e)}}}const pe='{"title":"Hands-on exercise","local":"hands-on-exercise","sections":[],"depth":1}';function fe(C){return ee(()=>{new URLSearchParams(window.location.search).get("fw")}),[]}class be extends ne{constructor(i){super(),oe(this,i,fe,ue,Z,{})}}export{be as component};
