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구글 마인트맵 -  How to set up MindMup 2.0 to open files on double-click

 

drive.mindmup.com/

 

MindMup 2

Unable to start MindMup There was a problem loading this page. If you are not experiencing network problems at the moment, then your browser is perhaps too old to work with MindMup. Try updating your browser to fix this issue.

drive.mindmup.com

youtu.be/c88_WauKevs

Great for individual note-taking

  • Capture ideas at the speed of thought: MindMup has powerful keyboard shortcuts to speed up your work, and the interface is optimised for frictionless work and designed to get out of your way.
  • Access your ideas from anywhere: Your mind maps are stored in Google's cloud infrastructure, so you can use them from any device and any location. The user interface adjusts automatically to screen sizes and input devices, so it will work great both on your desktop and on your mobile devices.
  • Add images easily: Easily insert images from Google Drive albums. If your mobile phone is synchronised with Google Drive, just snap, click, and they are in your mind map.

Do more with mind maps, faster

  • Capture ideas at the speed of thought: MindMup has powerful keyboard shortcuts to speed up your work, and the interface is optimised for frictionless work and designed to get out of your way.
  • Make slideshows and articles: If you plan presentations or prepare for writing using mind maps, MindMup will help you take your thoughts into a slideshow or a document outline quickly.
  • Access your ideas from anywhere: Your mind maps are available everywhere, instantly, from the cloud.
  • Connect team documents visually: link to other project documents on Google Drive easily, and you'll be able to preview them in the map and use the mindmap as a central overview of your work.

Great for teams and classrooms

  • Work safely and securely: All the data is stored on Google Drive, directly from the browser. The access is completely controlled by Google Apps authentication, so you can easily control who can read or modify the map. MindMup does not have any third-party ads and does not send any private information to third parties.
  • Easy to administer: Administrators can easily enable or block MindMup similar to any other Google Apps for Domains/Education application. Google authentication is used throughout the application, so there are no separate accounts to manage. The entire domain can easily be authorised for MindMup Gold.
  • Get started easily: The user interface is simple and intuitive, and even young students will be able to use it on their own without much help.
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마인드맵소프트웨어: Mind Maps | MindMeister

 

www.mindmeister.com/

 

MindMeister: 온라인 마인드맵과 브레인스토밍

온라인 마인드맵 소프트웨어의 선두주자 MindMeister를 이용하시면 마인드맵을 만들고, 공유하고 온라인에서 협업하실 수 있을 뿐만 아니라 아이폰,아이패드나 안드로이드로도 앱을 통해 사용하

www.mindmeister.com

 

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StreamingRecognitionResult

A streaming speech recognition result corresponding to a portion of the audio that is currently being processed.

Fields

 

#alternatives

#channel_tag

 

alternatives[]

SpeechRecognitionAlternative

May contain one or more recognition hypotheses (up to the maximum specified in max_alternatives). These alternatives are ordered in terms of accuracy, with the top (first) alternative being the most probable, as ranked by the recognizer.
is_final

bool

If false, this StreamingRecognitionResult represents an interim result that may change. If true, this is the final time the speech service will return this particular StreamingRecognitionResult, the recognizer will not return any further hypotheses for this portion of the transcript and corresponding audio.
stability

float

An estimate of the likelihood that the recognizer will not change its guess about this interim result. Values range from 0.0 (completely unstable) to 1.0 (completely stable). This field is only provided for interim results (is_final=false). The default of 0.0 is a sentinel value indicating stability was not set.
result_end_time

Duration

Time offset of the end of this result relative to the beginning of the audio.
channel_tag

int32

For multi-channel audio, this is the channel number corresponding to the recognized result for the audio from that channel. For audio_channel_count = N, its output values can range from '1' to 'N'.

https://cloud.google.com/speech-to-text/docs/reference/rpc/google.cloud.speech.v1#streamingrecognitionresult

 

Package google.cloud.speech.v1  |  Cloud Speech-to-Text 문서

phrases[] string A list of strings containing words and phrases "hints" so that the speech recognition is more likely to recognize them. This can be used to improve the accuracy for specific words and phrases, for example, if specific commands are typicall

cloud.google.com

 

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Package google.cloud.speech.v1

RecognitionConfig

Provides information to the recognizer that specifies how to process the request.

Fields

encoding

AudioEncoding

Encoding of audio data sent in all RecognitionAudio messages. This field is optional for FLAC and WAV audio files and required for all other audio formats. For details, see AudioEncoding.
sample_rate_hertz

int32

Sample rate in Hertz of the audio data sent in all RecognitionAudio messages. Valid values are: 8000-48000. 16000 is optimal. For best results, set the sampling rate of the audio source to 16000 Hz. If that's not possible, use the native sample rate of the audio source (instead of re-sampling). This field is optional for FLAC and WAV audio files, but is required for all other audio formats. For details, see AudioEncoding.
audio_channel_count

int32

The number of channels in the input audio data. ONLY set this for MULTI-CHANNEL recognition. Valid values for LINEAR16 and FLAC are 1-8. Valid values for OGG_OPUS are '1'-'254'. Valid value for MULAW, AMR, AMR_WB and SPEEX_WITH_HEADER_BYTE is only 1. If 0 or omitted, defaults to one channel (mono). Note: We only recognize the first channel by default. To perform independent recognition on each channel set enable_separate_recognition_per_channel to 'true'.
enable_separate_recognition_per_channel

bool

This needs to be set to true explicitly and audio_channel_count > 1 to get each channel recognized separately. The recognition result will contain a channel_tag field to state which channel that result belongs to. If this is not true, we will only recognize the first channel. The request is billed cumulatively for all channels recognized: audio_channel_count multiplied by the length of the audio.
language_code

string

Required. The language of the supplied audio as a BCP-47 language tag. Example: "en-US". See Language Support for a list of the currently supported language codes.
max_alternatives

int32

Maximum number of recognition hypotheses to be returned. Specifically, the maximum number of SpeechRecognitionAlternative messages within each SpeechRecognitionResult. The server may return fewer than max_alternatives. Valid values are 0-30. A value of 0 or 1 will return a maximum of one. If omitted, will return a maximum of one.
profanity_filter

bool

If set to true, the server will attempt to filter out profanities, replacing all but the initial character in each filtered word with asterisks, e.g. "f***". If set to false or omitted, profanities won't be filtered out.
speech_contexts[]

SpeechContext

Array of SpeechContext. A means to provide context to assist the speech recognition. For more information, see speech adaptation.
enable_word_time_offsets

bool

If true, the top result includes a list of words and the start and end time offsets (timestamps) for those words. If false, no word-level time offset information is returned. The default is false.
enable_automatic_punctuation

bool

If 'true', adds punctuation to recognition result hypotheses. This feature is only available in select languages. Setting this for requests in other languages has no effect at all. The default 'false' value does not add punctuation to result hypotheses.
diarization_config

SpeakerDiarizationConfig

Config to enable speaker diarization and set additional parameters to make diarization better suited for your application. Note: When this is enabled, we send all the words from the beginning of the audio for the top alternative in every consecutive STREAMING responses. This is done in order to improve our speaker tags as our models learn to identify the speakers in the conversation over time. For non-streaming requests, the diarization results will be provided only in the top alternative of the FINAL SpeechRecognitionResult.
metadata

RecognitionMetadata

Metadata regarding this request.
model

string

Which model to select for the given request. Select the model best suited to your domain to get best results. If a model is not explicitly specified, then we auto-select a model based on the parameters in the RecognitionConfig.

 
use_enhanced

bool

Set to true to use an enhanced model for speech recognition. If use_enhanced is set to true and the model field is not set, then an appropriate enhanced model is chosen if an enhanced model exists for the audio.

If use_enhanced is true and an enhanced version of the specified model does not exist, then the speech is recognized using the standard version of the specified model.

 

 

 

 

https://cloud.google.com/speech-to-text/docs/reference/rpc/google.cloud.speech.v1#recognitionconfig

 

Package google.cloud.speech.v1  |  Cloud Speech-to-Text 문서

phrases[] string A list of strings containing words and phrases "hints" so that the speech recognition is more likely to recognize them. This can be used to improve the accuracy for specific words and phrases, for example, if specific commands are typicall

cloud.google.com

 

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현재 시간, 일시

 

import datetime
 
now = datetime.datetime.now()
print(now)          # 2015-04-19 12:11:32.669083
 
nowDate = now.strftime('%Y-%m-%d')
print(nowDate)      # 2015-04-19
 
nowTime = now.strftime('%H:%M:%S')
print(nowTime)      # 12:11:32
 
nowDatetime = now.strftime('%Y-%m-%d %H:%M:%S')
print(nowDatetime)  # 2015-04-19 12:11:32
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여러 채널로 오디오 스크립트 작성

transcribe_multichannel.py 

이 페이지에서는 Speech-to-Text를 사용하여 둘 이상의 채널이 포함된 오디오 파일을 텍스트로 변환하는 방법을 설명합니다.

오디오 데이터에는 녹음된 화자에 대한 각각의 채널이 포함되어 있는 경우가 많습니다. 예를 들어 두 사람의 전화 통화를 녹음한 오디오라면 각 회선이 별도로 녹음된 채널 두 개가 포함될 수 있습니다.

여러 채널이 포함된 오디오 데이터를 텍스트로 변환하려면 Speech-to-Text API에 대한 요청에 채널 수를 제공해야 합니다. 요청의 audioChannelCount 필드를 오디오에 있는 채널 수로 설정합니다.

여러 채널이 포함된 요청을 보내면 Speech-to-Text가 오디오에 있는 서로 다른 채널을 식별하는 결과를 반환하며 channelTag 필드를 사용하여 각 결과를 대신하는 항목에 라벨을 지정합니다.

 

오디오 채널 설명 : https://cloud.google.com/speech-to-text/docs/multi-channel

 

여러 채널로 오디오 스크립트 작성  |  Cloud Speech-to-Text 문서  |  Google Cloud

이 페이지에서는 Speech-to-Text를 사용하여 둘 이상의 채널이 포함된 오디오 파일을 텍스트로 변환하는 방법을 설명합니다. 오디오 데이터에는 녹음된 화자에 대한 각각의 채널이 포함되어 있는

cloud.google.com

 

from google.cloud import speech

client = speech.SpeechClient()

with open(speech_file, "rb") as audio_file:
    content = audio_file.read()

audio = speech.RecognitionAudio(content=content)

config = speech.RecognitionConfig(
    encoding=speech.RecognitionConfig.AudioEncoding.LINEAR16,
    sample_rate_hertz=44100,
    language_code="en-US",
    audio_channel_count=2,
    enable_separate_recognition_per_channel=True,
)

response = client.recognize(config=config, audio=audio)

for i, result in enumerate(response.results):
    alternative = result.alternatives[0]
    print("-" * 20)
    print("First alternative of result {}".format(i))
    print(u"Transcript: {}".format(alternative.transcript))
    print(u"Channel Tag: {}".format(result.channel_tag))

 

github.com/googleapis/python-speech/blob/master/samples/snippets/transcribe_multichannel.py

 

googleapis/python-speech

Contribute to googleapis/python-speech development by creating an account on GitHub.

github.com

 

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