How to get word-level confidence for each word using MS Azure speech to text service? Currently, I am getting confidence value for sentence-level and I need word-level confidence for further processing.
You can retrieve the wordLevelConfidence by adding the ‘format=detailed’ & ‘wordLevelConfidence=true’ to the URI
For example, the language set to US English using the West US endpoint is: https://westus.stt.speech.microsoft.com/speech/recognition/conversation/cognitiveservices/v1?language=en-US&format=detailed&wordLevelConfidence=true.
If you use the SDK:
var config = SpeechConfig.FromSubscription(sub, "westeurope");
config.SetServiceProperty("wordLevelConfidence", "true", ServicePropertyChannel.UriQueryParameter);
//config.RequestWordLevelTimestamps(); in case you also want wordleveltimestamps
config.OutputFormat = OutputFormat.Detailed;
the word confidence values are not part of the result directly, Take a look at the below for complete result in JSON form.
recognizer.Recognized += (s, e) =>
{
var j = e.Result.Properties.GetProperty(PropertyId.SpeechServiceResponse_JsonResult);
By using this code: setServiceProperty("wordLevelConfidence","true", ServicePropertyChannel.UriQueryParameter);
This is how I did it
SpeechConfig config = SpeechConfig.fromSubscription(speechSubscriptionKey, serviceRegion);
config.setServiceProperty("wordLevelConfidence","true", ServicePropertyChannel.UriQueryParameter);
config.setServiceProperty("format", "detailed", ServicePropertyChannel.UriQueryParameter); //you have to do it in this order
And this to get the results back
PropertyCollection properties = result.getProperties();
String property = properties.getProperty(PropertyId.SpeechServiceResponse_JsonResult);
Related
I am using Form recognizer and power skill code AnalyzeFormV2 provided by microsoft in the documentation to create a custom skill to index pdf contents. I used the labelling tool to train the data using custom labels. Some of the data in the pdf are numerical for which I am selecting the type as 'number' in the labelling tool.
After training the form recognizer returns the numerical fields as :
"TotalCredit": {
"type": "number",
"text": "350.00",
"page": 1,
"boundingBox": [
7.365,
5.755,
7.705,
5.755,
7.705,
5.855,
7.365,
5.855
],
"confidence": 0.799
}
The AnalyzeForm API using the azure power skill returns the field like this :
"TotalCredit": null
It returns all other fields which are string correctly.
Is it a bug of the power skill code? The code uses recognized[v] = field.value to assign the values to the mapped labels. This field.value comes from some 'form_recognizer_client' library. So I dont know how to transform the value to the needed format.
Any thoughts/help on this?
This is a bug, the line should be updated to
recognized[v] = field.value or field.value_data.text
Sometimes the form recognizer is not able to recognize numeric text. That's why it shows the value as null. I added field.value_data.text and changed it to float in the power skills code. This worked for me.
if field.value_type == 'string':
val = field.value
elif field.value_type == 'float':
text = field.value_data.text
val = text.replace(',','')
val = float(val)
I've just started my research on the "Azure FHIR SQL Server Version".
I had some issues trying to get the Json Resource in plain text, since It is stored compressed in the database (as shown in the following lines):
select r.RawResource from dbo.Resource r where r.IsHistory=0 and r.IsDeleted=0;
RAWRESOURCE
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
I tried different ways to get it, however no one was successful.
select cast(r.RawResource as varchar(max)) VarcharResource,
CONVERT(varchar(max), r.RawResource, 0) VarcharResource2
from dbo.Resource r where r.IsHistory=0 and r.IsDeleted=0;
VarcharResource2
‹ „’ËNÂP†çQš®4A""÷àJBtaŒÈθ(-`n)… „w÷›9§Ð4çtfÎÌ?ÿ\J&ÙÈJ¶H1òH>eÍ?”;Î ëL""YJ*_üsþ+´P*œTïW—†´‰Š¤#M1x1R{""]¤1ÖHZHôûTjÈÙð¸9úž[±ÜdͽErùfx,9™Ù?”cÉIߔ锣>ófH;üçàõÕaÔâ«s:v·9Šõnh(ÒÎGä i´¾-y]”H}pSëSŒ=0ÖΪ¿JÍÕ§R{qÌþ‹=tΉ™Á⤪3ÓM¼5d‚6'eW9S÷u×äšM>íB›»ë»xS¥†ó˜/dYÇ5o-³íZÉ=ó*b«%ûË™¦øîÿÈœä äÑ{ÿÌ,ás{]tXó¸;íyì*ñODìü¦2´J,˃ç5ÃRµi¡à¨±ëc1Ÿ”œjÓg4ÚÕ±&ÞíñÜz£[úÛ/ ½ã½µG[Ûâ¬Äïô(ß ÿÿ
Anybody knows the correct way to get back the Json in plain text?
Thanks
The resources are Gzipped, so something like:
string rawResource;
using (rawResourceStream)
using (var gzipStream = new GZipStream(rawResourceStream, CompressionMode.Decompress))
using (var reader = new StreamReader(gzipStream, ResourceEncoding))
{
rawResource = await reader.ReadToEndAsync();
}
I want to parse url attribute from the XML and show image in image control (the one reffered to by the URL) in listbox from the following feed link: http://feeds.bbci.co.uk/news/rss.xml
My code is:
var ComingNewsFromUri = from rss in XElement.Parse(e.Result).Descendants("item")
select new NewsItems
{
Title = rss.Element("title").Value,
PubDate = rss.Element("pubDate").Value,
Description = rss.Element("description").Value
};
For RSS, I would recommend using SyndicationFeed and SyndicationItem....does all the parsing and converting to objects automatically and brilliantly for you.
http://ryanhayes.net/blog/how-to-build-an-rss-feed-reader-in-windows-phone-7part-i-retrieving-parsing-and-displaying-post-titles/
I have an RSS feed app on the store myself using SyndicationFeed and it is very reliable and convenient.
Here is another sample by Microsoft
http://code.msdn.microsoft.com/wpapps/RSS-Reader-Sample-1702775f
I am using flickr api in order to count the how many times a tag occur. I want this information in order to calculate the Normalized Google Distance. I am using this query in my java code:
http://api.flickr.com/services/rest/?method=flickr.photos.search&api_key=XXXXXXX&format=json&tags=bank
But i don't get good results. For example when i search "bank" the count value is 357439, when i search "credit" the count value is 59288, but when i am search for "bank credit" the count value is only 2. When i searching with the search box at flickr.com for "bank credit" i get a lot of results. But as far as i can see the query it uses is
http://www.flickr.com/search/?q=bank%20credit
which i am not able to use through my java code. I am trying to pass this
http://api.flickr.com/services/rest/?method=flickr.photos.search&api_key=XXXXXXX&format=json&q=bank
and it says
Parameterless searches have been disabled. Please use flickr.photos.getRecent instead
How can i solve this problem?
Your generated url is incorrect
http://api.flickr.com/services/rest/method=flickr.photos.search&api_key=XXXXXXX&format=json&q=bank
is missing the question mark
http://api.flickr.com/services/rest/?method=flickr.photos.search&api_key=XXXXXXX&format=json&q=bank
UPDATE based on OP comments:
I didn't see you had the question mark on the top url string. Looking at it again, I did realize you are not passing in any valid parameters. "q" isn't one of the listed parameters on the search api page. Try something like below to search photos with "bank" tag
http://api.flickr.com/services/rest/?method=flickr.photos.search&api_key=XXXXXXX&format=json&tags=bank
or one with bank in description/title
http://api.flickr.com/services/rest/?method=flickr.photos.search&api_key=XXXXXXX&format=json&text=bank
I got the same error. but when I added media = photos in the parameters, it got resolved.
e.g. :
baseurl = "https://api.flickr.com/services/rest/"
params_d['api_key'] = 'XXXXXXX'
params_d['method'] = 'flickr.photos.search'
params_d['tag'] = "river,mountains"
params_d['tag_mode'] = 'all'
params_d['per_page'] = 5
params_d['media'] = "photos"
params_d['nojsoncallback'] = 1
params_d['format'] = 'json'
resp = requests.get(baseurl, params = params_d)
We are working on integrating Solr 3.6 to an eCommerce site. We have indexed data & search is performing really good.
We have some difficulties figuring how to use Predictive Search / Auto Complete Search Suggestion. Also interested to learn the best practices for implementing this feature.
Our goal is to offer predictive search similar to http://www.amazon.com/, but don't know how to implement it with Solr. More specifically I want to understand how to build those terms from Solr, or is it managed by something else external to solr? How the dictionary should be built for offering these kind of suggestions? Moreover, for some field, search should offer to search in category. Try typing "xper" into Amazon search box, and you will note that apart from xperia, xperia s, xperia p, it also list xperia s in Cell phones & accessories, which is a category.
Using a custom dictionary this would be difficult to manage. Or may be we don't know how to do it correctly. Looking to you to guide us on how best utilize solr to achieve this kind of suggestive search.
I would suggest you a couple of blogpost:
This one which shows you a really nice complete solution which works well but requires some additional work to be made, and uses a specific lucene index (solr core) for that specific purpose
I used the Highlight approach because the facet.prefix one is too heavy for big index, and the other ones had few or unclear documentation (i'm a stupid programmer)
So let's suppose the user has just typed "aaa bbb ccc"
Our autocomplete function (java/javascript) will call solr using the following params
q="aaa bbb"~100 ...base query, all the typed words except the last
fq=ccc* ...suggest word filter using last typed word
hl=true
hl.q=ccc* ...highlight word will be the one to suggest
fl=NONE ...return empty docs in result tag
hl.pre=### ...escape chars to locate highlight word in the response
hl.post=### ...see above
you can also control the number of suggestion with 'rows' and 'hl.fragsize' parameters
the highlight words in each document will be the right candidates for the suggestion with "aaa bbb" string
more suggestion words are the ones before/after the highlight words and, of course, you can implement more filters to extract valid words, avoid duplicates, limit suggestions
if interested i can send you some examples...
EDITED: Some further details about the approach
The portion of example i give supposes the 'autocomplete' mechanism given by jquery: we invoke a jsp (or a servlet) inside a web application passing as request param 'q' the words just typed by user.
This is the code of the jsp
ByteArrayInputStream is=null; // Used to manage Solr response
try{
StringBuffer queryUrl=new StringBuffer('putHereTheUrlOfSolrServer');
queryUrl.append("/select?wt=xml");
String typedWords=request.getParameter("q");
String base="";
if(typedWords.indexOf(" ")<=0) {
// No space typed by user: the 'easy case'
queryUrl.append("&q=text:");
queryUrl.append(URLEncoder.encode(typedWords+"*", "UTF-8"));
queryUrl.append("&hl.q=text:"+URLEncoder.encode(typedWords+"*", "UTF-8"));
} else {
// Space chars present
// we split the search in base phrase and last typed word
base=typedWords.substring(0,typedWords.lastIndexOf(" "));
queryUrl.append("&q=text:");
if(base.indexOf(" ")>0)
queryUrl.append("\""+URLEncoder.encode(base, "UTF-8")+"\"~1000");
else
queryUrl.append(URLEncoder.encode(base, "UTF-8"));
typedWords=typedWords.substring(typedWords.lastIndexOf(" ")+1);
queryUrl.append("&fq=text:"+URLEncoder.encode(typedWords+"*", "UTF-8"));
queryUrl.append("&hl.q=text:"+URLEncoder.encode(typedWords+"*", "UTF-8"));
}
// The additional parameters to control the solr response
queryUrl.append("&rows="+suggestPageSize); // Number of results returned, a parameter to control the number of suggestions
queryUrl.append("&fl=A_FIELD_NAME_THAT_DOES_NOT_EXIST"); // Interested only in highlights section, Solr return a 'light' answer
queryUrl.append("&start=0"); // Use only first page of results
queryUrl.append("&hl=true"); // Enable highlights feature
queryUrl.append("&hl.simple.pre=***"); // Use *** as 'highlight border'
queryUrl.append("&hl.simple.post=***"); // Use *** as 'highlight border'
queryUrl.append("&hl.fragsize="+suggestFragSize); // Another parameter to control the number of suggestions
queryUrl.append("&hl.fl=content,title"); // Look for result only in some fields
queryUrl.append("&facet=false"); // Disable facets
/* Omitted section: use a new URL(queryUrl.toString()) to get the solr response inside a byte array */
is=new ByteArrayInputStream(solrResponseByteArray);
DocumentBuilderFactory dbFactory = DocumentBuilderFactory.newInstance();
DocumentBuilder dBuilder = dbFactory.newDocumentBuilder();
Document doc = dBuilder.parse(is);
XPathFactory xPathfactory = XPathFactory.newInstance();
XPath xpath = xPathfactory.newXPath();
XPathExpression expr = xpath.compile("//response/lst[#name=\"highlighting\"]/lst/arr[#name=\"content\"]/str");
NodeList valueList = (NodeList) expr.evaluate(doc, XPathConstants.NODESET);
Vector<String> suggestions=new Vector<String>();
for (int j = 0; j < valueList.getLength(); ++j) {
Element value = (Element) valueList.item(j);
String[] result=value.getTextContent().split("\\*\\*\\*");
for(int k=0;k<result.length;k++){
String suggestedWord=result[k].toLowerCase();
if((k%2)!=0){
//Highlighted words management
if(suggestedWord.length()>=suggestedWord.length() && !suggestions.contains(suggestedWord))
suggestions.add(suggestedWord);
}else{
/* Words before/after highlighted words
we can put these words inside another vector
and use them if not enough suggestions */
}
}
}
/* Finally we build a Json Answer to be managed by our jquery function */
out.print(request.getParameter("json.wrf")+"({ \"suggestions\" : [");
boolean firstSugg=true;
for(String suggestionW:suggestions) {
out.print((firstSugg?" ":" ,"));
out.print("{ \"suggest\" : \"");
if(base.length()>0) {
out.print(base);
out.print(" ");
}
out.print(suggestionW+"\" }");
firstSugg=false;
}
out.print(" ]})");
}catch (Exception x) {
System.err.println("Exception during main process: " + x);
x.printStackTrace();
}finally{
//Gracefully close streams//
try{is.close();}catch(Exception x){;}
}
Hope to be helpfull,
Nik
This might help you out.I am trying to do the same.
http://solr.pl/en/2010/10/18/solr-and-autocomplete-part-1/