GCP Cloud Functionsの'connection error'の原因が不明

Cloud Functionsで特定のGCSバケットへのファイルアップロードをトリガーとして
そのファイルがflacファイルであれば、Speech APIを使って翻訳テキストを同じGCSバケットに
返すような処理を書こうとしています。

ただ、Function execution took 10764 ms, finished with status: 'connection error'の
ようなエラーが出てしまい、原因が全く検討がつきません。

考えうる原因についてご教示いただけますと幸いです。コードは以下の通りです。

node.js
1/**
2 * Triggered from a message on a Cloud Storage bucket.
3 *
4 * @param {!Object} event The Cloud Functions event.
5 * @param {!Function} The callback function.
6 */
7exports.processFile = (event, callback) => {
8
9    // Imports the Google Cloud client library
10    const speech = require('@google-cloud/speech');
11    const storage = require('@google-cloud/storage')();
12
13    // Instantiates a client
14    const client = new speech.SpeechClient();
15
16    // Get Information about put object of Cloud Storage 
17    const uploadedObject = event.data; // The Cloud Storage object.
18    const gcsUri = 'gs://' + uploadedObject.bucket + '/' + uploadedObject.name; // Uploaded object's URI.
19    const contentType = uploadedObject.contentType; // Object's content type.
20
21    console.log('URI of processing file : ' + gcsUri);
22    console.log('Type of processing file : ' + contentType);
23
24    // Except for audio file, expire function.
25    if(contentType === undefined){
26      console.log('Content-type of uploaded file is unclear. This function does nothing.');
27      process.exit(0);
28    } else if(contentType.indexOf(/audio/) === -1){
29      console.log('Uploaded file is not audio file. This function does nothing.');
30      process.exit(0);
31    }
32
33    // Configure about GCE object which is saved translated text.
34    // TODO: Now, the Quality of naming file is slipshod.
35    const textObject = storage.bucket(object.bucket).file('translated.txt');
36
37    // The encoding of the audio file, e.g. 'LINEAR16'
38    const encoding = 'FLAC';
39    // This param is optional for flac. The sample rate of the audio file in hertz, e.g. 16000.
40    // const sampleRateHertz = 44100;
41    // The BCP-47 language code to use, e.g. 'en-US'
42    const languageCode = 'ja-JP';
43
44    const config = {
45      encoding: encoding,
46      // sampleRateHertz: sampleRateHertz,
47      languageCode: languageCode
48    };
49
50    const audio = {
51      uri: gcsUri
52    };
53
54    const request = {
55      config: config,
56      audio: audio
57    };
58
59    // Detects speech in the audio file. This creates a recognition job that you
60    // can wait for now, or get its result later.
61    client.longRunningRecognize(request)
62      .then((data) => {
63        const operation = data[0];
64        // Get a Promise representation of the final result of the job
65        return operation.promise();
66      })
67      .then((data) => {
68        const response = data[0];
69        const transcription = response.results.map(result =>
70            result.alternatives[0].transcript).join('\n');
71        console.log('Transcription: ${transcription}');
72        return textObject.save(transcription)
73      })
74      .then(() => {
75        console.log('File saved.');
76      })
77      .catch((err) => {
78        console.error('ERROR:', err);
79      });
80    // callback();
81};