我使用Google Speech Recognizer API开发了基于JavaScript的Web应用程序。 主要语言应该是希伯来语，并且应该帮助医生编写医学诊断。 问题是，如果我说英语中的医学单词如C.T或糖尿病，用专业语言应该用英语说，它用希伯来语写英文单词。 我的问题是，如果有任何选项来定义多语言选项或定义语言优先级，当它检测到不熟悉的单词时，它将尝试第二个选择????
请帮帮我谢谢！
这是我的JavaScript代码：
var langs =
[['Afrikaans', ['af-ZA']],
['Hebrew', ['he-IL']],
['Bahasa Melayu', ['ms-MY']],
['Català', ['ca-ES']],
['Čeština', ['cs-CZ']],
['Deutsch', ['de-DE']],
['English', ['en-AU', 'Australia'],
['en-CA', 'Canada'],
['en-IN', 'India'],
['en-NZ', 'New Zealand'],
['en-ZA', 'South Africa'],
['en-GB', 'United Kingdom'],
['en-US', 'United States']],
['Español', ['es-AR', 'Argentina'],
['es-BO', 'Bolivia'],
['es-CL', 'Chile'],
['es-CO', 'Colombia'],
['es-CR', 'Costa Rica'],
['es-EC', 'Ecuador'],
['es-SV', 'El Salvador'],
['es-ES', 'España'],
['es-US', 'Estados Unidos'],
['es-GT', 'Guatemala'],
['es-HN', 'Honduras'],
['es-MX', 'México'],
['es-NI', 'Nicaragua'],
['es-PA', 'Panamá'],
['es-PY', 'Paraguay'],
['es-PE', 'Perú'],
['es-PR', 'Puerto Rico'],
['es-DO', 'República Dominicana'],
['es-UY', 'Uruguay'],
['es-VE', 'Venezuela']],
['Euskara', ['eu-ES']],
['Français', ['fr-FR']],
['Galego', ['gl-ES']],
['Hrvatski', ['hr_HR']],
['IsiZulu', ['zu-ZA']],
['Íslenska', ['is-IS']],
['Italiano', ['it-IT', 'Italia'],
['it-CH', 'Svizzera']],
['Magyar', ['hu-HU']],
['Nederlands', ['nl-NL']],
['Norsk bokmål', ['nb-NO']],
['Polski', ['pl-PL']],
['Português', ['pt-BR', 'Brasil'],
['pt-PT', 'Portugal']],
['Română', ['ro-RO']],
['Slovenčina', ['sk-SK']],
['Suomi', ['fi-FI']],
['Svenska', ['sv-SE']],
['Türkçe', ['tr-TR']],
['български', ['bg-BG']],
['Pусский', ['ru-RU']],
['Српски', ['sr-RS']],
['한국어', ['ko-KR']],
['中文', ['cmn-Hans-CN', '普通话 (中国大陆)'],
['cmn-Hans-HK', '普通话 (香港)'],
['cmn-Hant-TW', '中文 (台灣)'],
['yue-Hant-HK', '粵語 (香港)']],
['日本語', ['ja-JP']],
['Lingua latīna', ['la']]];
for (var i = 0; i < langs.length; i++) {
select_language.options[i] = new Option(langs[i][0], i);
}
select_language.selectedIndex = 1;
updateCountry();
select_dialect.selectedIndex = 1;
showInfo('info_start');
function updateCountry() {
for (var i = select_dialect.options.length - 1; i >= 0; i--) {
select_dialect.remove(i);
}
var list = langs[select_language.selectedIndex];
for (var i = 1; i < list.length; i++) {
select_dialect.options.add(new Option(list[i][1], list[i][0]));
}
select_dialect.style.visibility = list[1].length == 1 ? 'hidden' : 'visible';
}
var create_email = false;
var final_transcript = '';
var recognizing = false;
var ignore_onend;
var start_timestamp;
if (!('webkitSpeechRecognition' in window)) {
console.log("before upgrade")
upgrade();
} else {
start_button.style.display = 'inline-block';
var recognition = new webkitSpeechRecognition();
recognition.continuous = true;
recognition.interimResults = true;
recognition.onstart = function() {
recognizing = true;
showInfo('info_speak_now');
console.log("webkitSpeechRecognition")
start_img.src = '/static/Mic_MicroPhone_Mute.PNG';
start_pic=document.getElementById("start_img")
start_pic.style.height="59px";
start_pic.style.width="43px";
};
recognition.onerror = function(event) {
if (event.error == 'no-speech') {
console.log("event error");
start_img.src = '/static/mic.png';
showInfo('info_no_speech');
ignore_onend = true;
}
if (event.error == 'audio-capture') {
console.log("event caputre");
start_img.src = '/static/mic.png';
showInfo('info_no_microphone');
ignore_onend = true;
}
if (event.error == 'not-allowed') {
console.log("even not allowed");
if (event.timeStamp - start_timestamp < 100) {
showInfo('info_blocked');
} else {
showInfo('info_denied');
}
ignore_onend = true;
}
};
recognition.onend = function() {
recognizing = false;
if (ignore_onend) {
return;
}
console.log("init mic image");
start_img.src = '/static/mic.png';
if (!final_transcript) {
showInfo('info_start');
return;
}
showInfo('');
// if (window.getSelection) {
// window.getSelection().removeAllRanges();
// var range = document.createRange();
// range.selectNode(document.getElementById('final_span'));
// window.getSelection().addRange(range);
// }
if (create_email) {
create_email = false;
createEmail();
}
};
recognition.onresult = function(event) {
var interim_transcript = '';
for (var i = event.resultIndex; i < event.results.length; ++i) {
if (event.results[i].isFinal) {
console.log("Final!!!!!!!!!!!!")
console.log(final_span.value+event.results[i][0].transcript);
final_transcript = final_span.value+event.results[i][0].transcript;
final_span.value=final_transcript;
} else {
interim_transcript += event.results[i][0].transcript;
}
}
final_transcript = capitalize(final_transcript);
console.log("interim_transcript :");
console.log(interim_transcript);
console.log("final_transcript :");
console.log(final_transcript);
// final_span.value = linebreak(interim_transcript);
if (final_transcript) {
console.log("final transcript true");
// final_span.value= linebreak(final_transcript);
}
if (final_transcript || interim_transcript) {
showButtons('inline-block');
}
};
}
function upgrade() {
start_button.style.visibility = 'hidden';
showInfo('info_upgrade');
}
var two_line = /\n\n/g;
var one_line = /\n/g;
function linebreak(s) {
return s.replace(two_line, '<p></p>').replace(one_line, '<br>');
}
var first_char = /\S/;
function capitalize(s) {
return s.replace(first_char, function(m) { return m.toUpperCase(); });
}
function createEmail() {
var n = final_transcript.indexOf('\n');
if (n < 0 || n >= 80) {
n = 40 + final_transcript.substring(40).indexOf(' ');
}
var subject = encodeURI(final_transcript.substring(0, n));
var body = encodeURI(final_transcript.substring(n + 1));
textarea_value=document.getElementById("final_span").value;
window.location.href = 'mailto:?subject=' + "Puzzle-Soft Telemedicine - Speech Recognizer " + '&body=' + textarea_value;
}
function copyButton() {
if (recognizing) {
recognizing = false;
recognition.stop();
}
copy_button.style.display = 'none';
copy_info.style.display = 'inline-block';
showInfo('');
}
function emailButton() {
if (recognizing) {
create_email = true;
recognizing = false;
recognition.stop();
} else {
createEmail();
}
email_button.style.display = 'none';
email_info.style.display = 'inline-block';
showInfo('');
}
function startButton(event) {
if (recognizing) {
recognition.stop();
console.log("StartButton if")
return;
}
console.log("StartButton else")
final_transcript = '';
recognition.lang = select_dialect.value;
recognition.start();
ignore_onend = false;
// final_span.innerHTML = '';
// interim_span.innerHTML = '';
start_img.src = '/static/mic.png';
showInfo('info_allow');
showButtons('none');
start_timestamp = event.timeStamp;
}
function showInfo(s) {
if (s) {
for (var child = info.firstChild; child; child = child.nextSibling) {
if (child.style) {
child.style.display = child.id == s ? 'inline' : 'none';
}
}
info.style.visibility = 'visible';
} else {
info.style.visibility = 'hidden';
}
}
var current_style;
function showButtons(style) {
if (style == current_style) {
return;
}
current_style = style;
copy_button.style.display = style;
email_button.style.display = style;
copy_info.style.display = 'none';
email_info.style.display = 'none';
}
function ClearText() {
console.log("clear");
text_area_value=document.getElementById("final_span");
console.log(text_area_value);
console.log(text_area_value.value);
text_area_value.value='';
}
//var givevalue = function (my_key) {
// return dict[my_key];
//
// }
//
//js_json={'אדרנלypr': 'Olanzapine Teva', 'זיפאדהרה': 'Zypadhera', 'אומפראזול': 'Omeprazole', 'אומפרדקס': 'Omepradex', 'לוסק': 'Losec', 'אומפריקס': 'Omeprix', 'אומפרדקס Z': 'Omepradex Z', 'אומפרה': 'Omepra', 'אונדאנסטרון': 'Ondansetron', 'זופרן': 'Zofran', 'אודנטרון': 'Odnatron', 'אונדאנסטרון - פרזניוס': 'Ondansetron - Fresenius', 'אונדנסטרון אינובמד': 'Ondansetron Inovamed'}
//function replaceTextAreaDict() {
//textarea_result=document.getElementById("final_span");
// textarea_words=textarea_result.split(' ') ;
// for (var i = 0; i < textarea_result.length; i++) {
//
// }
//
//
//
// givevalue()
//
//}
//
//replaceTextAreaDict();
答案 0 :(得分：0)
你不能混合语言。
语音识别大致包含3部分 - ＆gt;声学模型，语言模型和字典。
声学模型是数据训练包含音频信号与语音之间关系的结果
字典包含单词及其发音方式，例如，单词TOP在一般语音识别字典上发音为“T AH P”。
语言模型是用于创建句子的单词之间的连接，例如单词“I”与“am”相关联，因此语音识别器很少（或从不）给出“我是”或“我是”的结果。
每种语言都有自己的声学模型（语音），词典（单词）和语言模型（句子），所以我们可以将它们混合起来。
问题是：它还可以吗？
答案是：是的！
您可以使用许多工具构建自己的语言（在本例中为医学语言），我已经尝试过一种名为CMU Sphinx / Pocket Sphinx的工具。您可以构建自己的模型，训练它，并从中制作一本字典。这将是很多工作，但你可以配置语音识别所需的任何东西。
任何平台实施的链接：https://github.com/cmusphinx